19th International Conference on Information Fusion - User contributions [en]

Schedule

2016-06-21T04:34:08Z

Hanebeck:

{| id="mp-upper" style="width: 100%; margin:4px 0 0 0; background:none; border-spacing: 0px;"

| class="MainPageBG" style="width:100%; border:1px solid #f2ea7e; background:#ffffe8; vertical-align:top; color:#000;" |
{| id="mp-left" style="width:100%; vertical-align:top; background:#ffffe8;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#fff7bd; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f2ea7e; text-align:left; color:#000; padding:0.2em 0.4em;">Room mapping</h2>
|-
| style="color:#000;" | <div id="mp-tfa" style="padding:2px 5px">
{| class="wikitable"
!style="text-align:center;background-color:#fff7bd;"| '''Room code'''
! style="text-align:center;background-color:#fff7bd;"| '''Room name'''
! style="text-align:center;background-color:#fff7bd;"| '''Capacity'''
|-
|style="text-align:center;background-color:#ffffe8;"| '''Room A'''
|style="text-align:center;background-color:#ffffe8;" | Großer Saal
|style="text-align:center;background-color:#ffffe8;" | 1100
|-
|style="text-align:center;background-color:#fff7bd;"| '''Room B'''
|style="text-align:center;background-color:#fff7bd;" | Ballsaal
|style="text-align:center;background-color:#fff7bd;" | 180
|-
|style="text-align:center;background-color:#ffffe8;"| '''Room C'''
|style="text-align:center;background-color:#ffffe8;" | Kammermusiksaal
|style="text-align:center;background-color:#ffffe8;" | 150
|-
|style="text-align:center;background-color:#fff7bd;"| '''Room D'''
|style="text-align:center;background-color:#fff7bd;" | Trübnersaal
|style="text-align:center;background-color:#fff7bd;" | 104
|-
|style="text-align:center;background-color:#ffffe8;"| '''Room E'''
|style="text-align:center;background-color:#ffffe8;" | Sebastian-Münster-Saal
|style="text-align:center;background-color:#ffffe8;" | 80
|-
|style="text-align:center;background-color:#fff7bd;"| '''Room F'''
|style="text-align:center;background-color:#fff7bd;" | Gustav-Mahler-Zimmer
|style="text-align:center;background-color:#fff7bd;" | 50
|-
|style="text-align:center;background-color:#ffffe8;"| '''Room G'''
|style="text-align:center;background-color:#ffffe8;" | Robert-Schumann-Zimmer
|style="text-align:center;background-color:#ffffe8;" | 50
|-
|style="text-align:center;background-color:#fff7bd;"| '''Room H'''
|style="text-align:center;background-color:#fff7bd;" | Hölderlinsaal
|style="text-align:center;background-color:#fff7bd;" | 50
|-
|style="text-align:center;background-color:#ffffe8;"| '''Room I'''
|style="text-align:center;background-color:#ffffe8;" | Stefan-George-Zimmer
|style="text-align:center;background-color:#ffffe8;" | 15
|-
|style="text-align:center;background-color:#fff7bd;"| '''Room K'''
|style="text-align:center;background-color:#fff7bd;" | Fürstenzimmer
|style="text-align:center;background-color:#fff7bd;" | 10
|}

</div>
|}
| style="border:1px solid transparent;" |<br />
|-


{| id="mp-upper" style="width: 100%; margin:4px 0 0 0; background:none; border-spacing: 0px;"
<div id="ss1">

| class="MainPageBG" style="width:100%; border:1px solid #d6bdde; background:#f7eff7; vertical-align:top; color:#000;" |
{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:125%; font-weight:bold; border:1px solid #d6bdde; text-align:left; color:#000; padding:0.2em 0.4em;">Tutorial day</h2>
|-
| style="color:#000;" | <div id="mp-tfa" style="padding:2px 5px">
{| class="wikitable"
! style="text-align:center;background-color:#e7deef;"|
! style="text-align:center;background-color:#e7deef;"| '''Tuesday, July 5'''
|-
|style="text-align:center;background-color:#f7eff7;" | 07:30
|style="text-align:center;background-color:#f7eff7;" | Welcome coffee
|-
|style="text-align:center;background-color:#e7deef;" | 08:30
|style="text-align:center;background-color:#e7deef;" | Tutorial session
|-
|style="text-align:center;background-color:#f7eff7;" | 11:30
|style="text-align:center;background-color:#f7eff7;" | Lunch break
|-
|style="text-align:center;background-color:#e7deef;" | 12:30
|style="text-align:center;background-color:#e7deef;" | Tutorial session
|-
|style="text-align:center;background-color:#f7eff7;" | 15:30
|style="text-align:center;background-color:#f7eff7;" | Coffee break
|-
|style="text-align:center;background-color:#e7deef;" | 16:00
|style="text-align:center;background-color:#e7deef;" | Tutorial session
|-
|style="text-align:center;background-color:#f7eff7;" | 19:00
|style="text-align:center;background-color:#f7eff7;" | Welcome reception
|-
|}

Link to [[Tutorials#timetable| Tutorials schedule]].
|-
|}
| style="border:1px solid transparent;" |<br />
|-


{| id="mp-upper" style="width: 100%; margin:4px 0 0 0; background:none; border-spacing: 0px;"

| class="MainPageBG" style="width:100%; border:1px solid #bdd6c6; background:#e7f7e7; vertical-align:top; color:#000;" |
{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#d6efd6; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #bdd6c6; text-align:left; color:#000; padding:0.2em 0.4em;">Main conference</h2>
|-
| style="color:#000;" | <div id="mp-tfa" style="padding:2px 5px">
{| class="wikitable"
! style="text-align:center;background-color:#d6efd6;"|
! style="text-align:center;background-color:#d6efd6;"| '''Wednesday, July 6'''

! style="text-align:center;background-color:#d6efd6;"| '''Thursday, July 7'''

! style="text-align:center;background-color:#d6efd6;"| '''Friday, July 8'''

|-
|style="text-align:center;background-color:#e7f7e7;" | 06:30
|style="text-align:center;background-color:#e7f7e7;" | -
|style="text-align:center;background-color:#e7f7e7;" | 5K run
|style="text-align:center;background-color:#e7f7e7;" | -
|-
|style="text-align:center;background-color:#d6efd6;" | 07:30
|colspan="3" style="text-align:center;background-color:#d6efd6;"| Welcome coffee
|-
|style="text-align:center;background-color:#e7f7e7;" | 08:30
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Welcome session (Großer Saal)
|-
|style="text-align:center;background-color:#d6efd6;" | 09:00
|colspan="3" style="text-align:center;background-color:#d6efd6;"| Plenary talk
|-
|style="text-align:center;background-color:#e7f7e7;" | 10:00
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Coffee break
|-
|style="text-align:center;background-color:#d6efd6;" | 10:30
|style="text-align:center;background-color:#d6efd6;" | Session I
|style="text-align:center;background-color:#d6efd6;" | Session I
|style="text-align:center;background-color:#d6efd6;" | Session I
|-
|style="text-align:center;background-color:#e7f7e7;" | 12:10
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Lunch
|-
|style="text-align:center;background-color:#d6efd6;" | 13:10
|style="text-align:center;background-color:#d6efd6;" | Session II
|style="text-align:center;background-color:#d6efd6;" | Session II
|style="text-align:center;background-color:#d6efd6;" | Session II
|-
|style="text-align:center;background-color:#e7f7e7;" | 14:50
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Coffee break
|-
|style="text-align:center;background-color:#d6efd6;" | 15:20
|style="text-align:center;background-color:#d6efd6;" | Session III
|style="text-align:center;background-color:#d6efd6;" | Session III
|style="text-align:center;background-color:#d6efd6;" | Session III
|-
|style="text-align:center;background-color:#e7f7e7;" | 17:00
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Break
|-
|style="text-align:center;background-color:#d6efd6;" | 17:30
|style="text-align:center;background-color:#d6efd6;" | -
|style="text-align:center;background-color:#d6efd6;" | Gala dinner
|style="text-align:center;background-color:#d6efd6;" | -
|-
|}

The detailed technical program can be found on the [http://edas.info/p22132 edas] website.
| style="border:1px solid transparent;" |<br />
|-

__NOTOC____NOEDITSECTION__

Schedule

2016-06-20T18:49:32Z

Hanebeck:

{| id="mp-upper" style="width: 100%; margin:4px 0 0 0; background:none; border-spacing: 0px;"

| class="MainPageBG" style="width:100%; border:1px solid #f2ea7e; background:#ffffe8; vertical-align:top; color:#000;" |
{| id="mp-left" style="width:100%; vertical-align:top; background:#ffffe8;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#fff7bd; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f2ea7e; text-align:left; color:#000; padding:0.2em 0.4em;">Room mapping</h2>
|-
| style="color:#000;" | <div id="mp-tfa" style="padding:2px 5px">
{| class="wikitable"
!style="text-align:center;background-color:#fff7bd;"| '''Room Code'''
! style="text-align:center;background-color:#fff7bd;"| '''Room name'''
! style="text-align:center;background-color:#fff7bd;"| '''Capacity'''
|-
|style="text-align:center;background-color:#ffffe8;"| '''Room A'''
|style="text-align:center;background-color:#ffffe8;" | Großer Saal
|style="text-align:center;background-color:#ffffe8;" | 1100
|-
|style="text-align:center;background-color:#fff7bd;"| '''Room B'''
|style="text-align:center;background-color:#fff7bd;" | Ballsaal
|style="text-align:center;background-color:#fff7bd;" | 180
|-
|style="text-align:center;background-color:#ffffe8;"| '''Room C'''
|style="text-align:center;background-color:#ffffe8;" | Kammermusiksaal
|style="text-align:center;background-color:#ffffe8;" | 150
|-
|style="text-align:center;background-color:#fff7bd;"| '''Room D'''
|style="text-align:center;background-color:#fff7bd;" | Trübnersaal
|style="text-align:center;background-color:#fff7bd;" | 104
|-
|style="text-align:center;background-color:#ffffe8;"| '''Room E'''
|style="text-align:center;background-color:#ffffe8;" | Sebastian-Münster-Saal
|style="text-align:center;background-color:#ffffe8;" | 80
|-
|style="text-align:center;background-color:#fff7bd;"| '''Room F'''
|style="text-align:center;background-color:#fff7bd;" | Gustav-Mahler-Zimmer
|style="text-align:center;background-color:#fff7bd;" | 50
|-
|style="text-align:center;background-color:#ffffe8;"| '''Room G'''
|style="text-align:center;background-color:#ffffe8;" | Robert-Schumann-Zimmer
|style="text-align:center;background-color:#ffffe8;" | 50
|-
|style="text-align:center;background-color:#fff7bd;"| '''Room H'''
|style="text-align:center;background-color:#fff7bd;" | Hölderlinsaal
|style="text-align:center;background-color:#fff7bd;" | 50
|-
|style="text-align:center;background-color:#ffffe8;"| '''Room I'''
|style="text-align:center;background-color:#ffffe8;" | Stefan-George-Zimmer
|style="text-align:center;background-color:#ffffe8;" | 15
|-
|style="text-align:center;background-color:#fff7bd;"| '''Room K'''
|style="text-align:center;background-color:#fff7bd;" | Fürstenzimmer
|style="text-align:center;background-color:#fff7bd;" | 10
|}

</div>
|}
| style="border:1px solid transparent;" |<br />
|-


{| id="mp-upper" style="width: 100%; margin:4px 0 0 0; background:none; border-spacing: 0px;"
<div id="ss1">

| class="MainPageBG" style="width:100%; border:1px solid #d6bdde; background:#f7eff7; vertical-align:top; color:#000;" |
{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:125%; font-weight:bold; border:1px solid #d6bdde; text-align:left; color:#000; padding:0.2em 0.4em;">Tutorial day</h2>
|-
| style="color:#000;" | <div id="mp-tfa" style="padding:2px 5px">
{| class="wikitable"
! style="text-align:center;background-color:#e7deef;"|
! style="text-align:center;background-color:#e7deef;"| '''Tuesday, July 5'''
|-
|style="text-align:center;background-color:#f7eff7;" | 07:30
|style="text-align:center;background-color:#f7eff7;" | Welcome coffee
|-
|style="text-align:center;background-color:#e7deef;" | 08:30
|style="text-align:center;background-color:#e7deef;" | Tutorial session
|-
|style="text-align:center;background-color:#f7eff7;" | 11:30
|style="text-align:center;background-color:#f7eff7;" | Lunch break
|-
|style="text-align:center;background-color:#e7deef;" | 12:30
|style="text-align:center;background-color:#e7deef;" | Tutorial session
|-
|style="text-align:center;background-color:#f7eff7;" | 15:30
|style="text-align:center;background-color:#f7eff7;" | Coffee break
|-
|style="text-align:center;background-color:#e7deef;" | 16:00
|style="text-align:center;background-color:#e7deef;" | Tutorial session
|-
|style="text-align:center;background-color:#f7eff7;" | 19:00
|style="text-align:center;background-color:#f7eff7;" | Welcome reception
|-
|}

Link to [[Tutorials#timetable| Tutorials schedule]].
|-
|}
| style="border:1px solid transparent;" |<br />
|-


{| id="mp-upper" style="width: 100%; margin:4px 0 0 0; background:none; border-spacing: 0px;"

| class="MainPageBG" style="width:100%; border:1px solid #bdd6c6; background:#e7f7e7; vertical-align:top; color:#000;" |
{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#d6efd6; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #bdd6c6; text-align:left; color:#000; padding:0.2em 0.4em;">Main conference</h2>
|-
| style="color:#000;" | <div id="mp-tfa" style="padding:2px 5px">
{| class="wikitable"
! style="text-align:center;background-color:#d6efd6;"|
! style="text-align:center;background-color:#d6efd6;"| '''Wednesday, July 6'''

! style="text-align:center;background-color:#d6efd6;"| '''Thursday, July 7'''

! style="text-align:center;background-color:#d6efd6;"| '''Friday, July 8'''

|-
|style="text-align:center;background-color:#e7f7e7;" | 06:30
|style="text-align:center;background-color:#e7f7e7;" | -
|style="text-align:center;background-color:#e7f7e7;" | 5K run
|style="text-align:center;background-color:#e7f7e7;" | -
|-
|style="text-align:center;background-color:#d6efd6;" | 07:30
|colspan="3" style="text-align:center;background-color:#d6efd6;"| Welcome coffee
|-
|style="text-align:center;background-color:#e7f7e7;" | 08:30
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Welcome session (Großer Saal)
|-
|style="text-align:center;background-color:#d6efd6;" | 09:00
|colspan="3" style="text-align:center;background-color:#d6efd6;"| Plenary talk
|-
|style="text-align:center;background-color:#e7f7e7;" | 10:00
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Coffee break
|-
|style="text-align:center;background-color:#d6efd6;" | 10:30
|style="text-align:center;background-color:#d6efd6;" | Session I
|style="text-align:center;background-color:#d6efd6;" | Session I
|style="text-align:center;background-color:#d6efd6;" | Session I
|-
|style="text-align:center;background-color:#e7f7e7;" | 12:10
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Lunch
|-
|style="text-align:center;background-color:#d6efd6;" | 13:10
|style="text-align:center;background-color:#d6efd6;" | Session II
|style="text-align:center;background-color:#d6efd6;" | Session II
|style="text-align:center;background-color:#d6efd6;" | Session II
|-
|style="text-align:center;background-color:#e7f7e7;" | 14:50
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Coffee break
|-
|style="text-align:center;background-color:#d6efd6;" | 15:20
|style="text-align:center;background-color:#d6efd6;" | Session III
|style="text-align:center;background-color:#d6efd6;" | Session III
|style="text-align:center;background-color:#d6efd6;" | Session III
|-
|style="text-align:center;background-color:#e7f7e7;" | 17:00
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Break
|-
|style="text-align:center;background-color:#d6efd6;" | 17:30
|style="text-align:center;background-color:#d6efd6;" | -
|style="text-align:center;background-color:#d6efd6;" | Gala dinner
|style="text-align:center;background-color:#d6efd6;" | -
|-
|}

The detailed technical program can be found on the [http://edas.info/p22132 edas] website.
| style="border:1px solid transparent;" |<br />
|-

__NOTOC____NOEDITSECTION__

Schedule

2016-06-20T14:45:51Z

Hanebeck:

{| id="mp-upper" style="width: 100%; margin:4px 0 0 0; background:none; border-spacing: 0px;"

| class="MainPageBG" style="width:100%; border:1px solid #f2ea7e; background:#ffffe8; vertical-align:top; color:#000;" |
{| id="mp-left" style="width:100%; vertical-align:top; background:#ffffe8;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#fff7bd; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f2ea7e; text-align:left; color:#000; padding:0.2em 0.4em;">Room mapping</h2>
|-
| style="color:#000;" | <div id="mp-tfa" style="padding:2px 5px">
{| class="wikitable"
!style="text-align:center;background-color:#fff7bd;"| '''Room'''
! style="text-align:center;background-color:#fff7bd;"| '''Room name'''
! style="text-align:center;background-color:#fff7bd;"| '''Capacity'''
|-
|style="text-align:center;background-color:#ffffe8;"| '''Room A'''
|style="text-align:center;background-color:#ffffe8;" | Großer Saal
|style="text-align:center;background-color:#ffffe8;" | 1100
|-
|style="text-align:center;background-color:#fff7bd;"| '''Room B'''
|style="text-align:center;background-color:#fff7bd;" | Ballsaal
|style="text-align:center;background-color:#fff7bd;" | 180
|-
|style="text-align:center;background-color:#ffffe8;"| '''Room C'''
|style="text-align:center;background-color:#ffffe8;" | Kammermusiksaal
|style="text-align:center;background-color:#ffffe8;" | 150
|-
|style="text-align:center;background-color:#fff7bd;"| '''Room D'''
|style="text-align:center;background-color:#fff7bd;" | Trübnersaal
|style="text-align:center;background-color:#fff7bd;" | 104
|-
|style="text-align:center;background-color:#ffffe8;"| '''Room E'''
|style="text-align:center;background-color:#ffffe8;" | Sebastian-Münster-Saal
|style="text-align:center;background-color:#ffffe8;" | 80
|-
|style="text-align:center;background-color:#fff7bd;"| '''Room F'''
|style="text-align:center;background-color:#fff7bd;" | Gustav-Mahler-Zimmer
|style="text-align:center;background-color:#fff7bd;" | 50
|-
|style="text-align:center;background-color:#ffffe8;"| '''Room G'''
|style="text-align:center;background-color:#ffffe8;" | Robert-Schumann-Zimmer
|style="text-align:center;background-color:#ffffe8;" | 50
|-
|style="text-align:center;background-color:#fff7bd;"| '''Room H'''
|style="text-align:center;background-color:#fff7bd;" | Hölderlinsaal
|style="text-align:center;background-color:#fff7bd;" | 50
|-
|style="text-align:center;background-color:#ffffe8;"| '''Room I'''
|style="text-align:center;background-color:#ffffe8;" | Stefan-George-Zimmer
|style="text-align:center;background-color:#ffffe8;" | 15
|-
|style="text-align:center;background-color:#fff7bd;"| '''Room K'''
|style="text-align:center;background-color:#fff7bd;" | Fürstenzimmer
|style="text-align:center;background-color:#fff7bd;" | 10
|}

</div>
|}
| style="border:1px solid transparent;" |<br />
|-


{| id="mp-upper" style="width: 100%; margin:4px 0 0 0; background:none; border-spacing: 0px;"
<div id="ss1">

| class="MainPageBG" style="width:100%; border:1px solid #d6bdde; background:#f7eff7; vertical-align:top; color:#000;" |
{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:125%; font-weight:bold; border:1px solid #d6bdde; text-align:left; color:#000; padding:0.2em 0.4em;">Tutorial day</h2>
|-
| style="color:#000;" | <div id="mp-tfa" style="padding:2px 5px">
{| class="wikitable"
! style="text-align:center;background-color:#e7deef;"|
! style="text-align:center;background-color:#e7deef;"| '''Tuesday, July 5'''
|-
|style="text-align:center;background-color:#f7eff7;" | 07:30
|style="text-align:center;background-color:#f7eff7;" | Welcome coffee
|-
|style="text-align:center;background-color:#e7deef;" | 08:30
|style="text-align:center;background-color:#e7deef;" | Tutorial session
|-
|style="text-align:center;background-color:#f7eff7;" | 11:30
|style="text-align:center;background-color:#f7eff7;" | Lunch break
|-
|style="text-align:center;background-color:#e7deef;" | 12:30
|style="text-align:center;background-color:#e7deef;" | Tutorial session
|-
|style="text-align:center;background-color:#f7eff7;" | 15:30
|style="text-align:center;background-color:#f7eff7;" | Coffee break
|-
|style="text-align:center;background-color:#e7deef;" | 16:00
|style="text-align:center;background-color:#e7deef;" | Tutorial session
|-
|style="text-align:center;background-color:#f7eff7;" | 19:00
|style="text-align:center;background-color:#f7eff7;" | Welcome reception
|-
|}

Link to [[Tutorials#timetable| Tutorials schedule]].
|-
|}
| style="border:1px solid transparent;" |<br />
|-


{| id="mp-upper" style="width: 100%; margin:4px 0 0 0; background:none; border-spacing: 0px;"

| class="MainPageBG" style="width:100%; border:1px solid #bdd6c6; background:#e7f7e7; vertical-align:top; color:#000;" |
{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#d6efd6; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #bdd6c6; text-align:left; color:#000; padding:0.2em 0.4em;">Main conference</h2>
|-
| style="color:#000;" | <div id="mp-tfa" style="padding:2px 5px">
{| class="wikitable"
! style="text-align:center;background-color:#d6efd6;"|
! style="text-align:center;background-color:#d6efd6;"| '''Wednesday, July 6'''

! style="text-align:center;background-color:#d6efd6;"| '''Thursday, July 7'''

! style="text-align:center;background-color:#d6efd6;"| '''Friday, July 8'''

|-
|style="text-align:center;background-color:#e7f7e7;" | 06:30
|style="text-align:center;background-color:#e7f7e7;" | -
|style="text-align:center;background-color:#e7f7e7;" | 5K run
|style="text-align:center;background-color:#e7f7e7;" | -
|-
|style="text-align:center;background-color:#d6efd6;" | 07:30
|colspan="3" style="text-align:center;background-color:#d6efd6;"| Welcome coffee
|-
|style="text-align:center;background-color:#e7f7e7;" | 08:30
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Welcome session (Großer Saal)
|-
|style="text-align:center;background-color:#d6efd6;" | 09:00
|colspan="3" style="text-align:center;background-color:#d6efd6;"| Plenary talk
|-
|style="text-align:center;background-color:#e7f7e7;" | 10:00
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Coffee break
|-
|style="text-align:center;background-color:#d6efd6;" | 10:30
|style="text-align:center;background-color:#d6efd6;" | Session I
|style="text-align:center;background-color:#d6efd6;" | Session I
|style="text-align:center;background-color:#d6efd6;" | Session I
|-
|style="text-align:center;background-color:#e7f7e7;" | 12:10
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Lunch
|-
|style="text-align:center;background-color:#d6efd6;" | 13:10
|style="text-align:center;background-color:#d6efd6;" | Session II
|style="text-align:center;background-color:#d6efd6;" | Session II
|style="text-align:center;background-color:#d6efd6;" | Session II
|-
|style="text-align:center;background-color:#e7f7e7;" | 14:50
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Coffee break
|-
|style="text-align:center;background-color:#d6efd6;" | 15:20
|style="text-align:center;background-color:#d6efd6;" | Session III
|style="text-align:center;background-color:#d6efd6;" | Session III
|style="text-align:center;background-color:#d6efd6;" | Session III
|-
|style="text-align:center;background-color:#e7f7e7;" | 17:00
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Break
|-
|style="text-align:center;background-color:#d6efd6;" | 17:30
|style="text-align:center;background-color:#d6efd6;" | -
|style="text-align:center;background-color:#d6efd6;" | Gala dinner
|style="text-align:center;background-color:#d6efd6;" | -
|-
|}

The detailed technical program can be found on the [http://edas.info/p22132 edas] website.
| style="border:1px solid transparent;" |<br />
|-

__NOTOC____NOEDITSECTION__

Schedule

2016-06-20T14:44:33Z

Hanebeck:

{| id="mp-upper" style="width: 100%; margin:4px 0 0 0; background:none; border-spacing: 0px;"

| class="MainPageBG" style="width:100%; border:1px solid #f2ea7e; background:#ffffe8; vertical-align:top; color:#000;" |
{| id="mp-left" style="width:100%; vertical-align:top; background:#ffffe8;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#fff7bd; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f2ea7e; text-align:left; color:#000; padding:0.2em 0.4em;">Room mapping</h2>
|-
| style="color:#000;" | <div id="mp-tfa" style="padding:2px 5px">
{| class="wikitable"
!style="text-align:center;background-color:#fff7bd;"| '''Room'''
! style="text-align:center;background-color:#fff7bd;"| '''Room name'''
! style="text-align:center;background-color:#fff7bd;"| '''Capacity'''
|-
|style="text-align:center;background-color:#ffffe8;"| '''Room A'''
|style="text-align:center;background-color:#ffffe8;" | Großer Saal
|style="text-align:center;background-color:#ffffe8;" | 1100
|-
|style="text-align:center;background-color:#fff7bd;"| '''Room B'''
|style="text-align:center;background-color:#fff7bd;" | Ballsaal
|style="text-align:center;background-color:#fff7bd;" | 180
|-
|style="text-align:center;background-color:#ffffe8;"| '''Room C'''
|style="text-align:center;background-color:#ffffe8;" | Kammermusiksaal
|style="text-align:center;background-color:#ffffe8;" | 150
|-
|style="text-align:center;background-color:#fff7bd;"| '''Room D'''
|style="text-align:center;background-color:#fff7bd;" | Trübnersaal
|style="text-align:center;background-color:#fff7bd;" | 104
|-
|style="text-align:center;background-color:#ffffe8;"| '''Room E'''
|style="text-align:center;background-color:#ffffe8;" | Sebastian-Münster-Saal
|style="text-align:center;background-color:#ffffe8;" | 80
|-
|style="text-align:center;background-color:#fff7bd;"| '''Room F'''
|style="text-align:center;background-color:#fff7bd;" | Gustav-Mahler-Zimmer
|style="text-align:center;background-color:#fff7bd;" | 50
|-
|style="text-align:center;background-color:#ffffe8;"| '''Room G'''
|style="text-align:center;background-color:#ffffe8;" | Robert-Schumann-Zimmer
|style="text-align:center;background-color:#ffffe8;" | 50
|-
|style="text-align:center;background-color:#fff7bd;"| '''Room H'''
|style="text-align:center;background-color:#fff7bd;" | Hölderlinsaal
|style="text-align:center;background-color:#fff7bd;" | 50
|-
|style="text-align:center;background-color:#ffffe8;"| '''Room I'''
|style="text-align:center;background-color:#ffffe8;" | Stefan-George-Zimmer
|style="text-align:center;background-color:#ffffe8;" | 15
|-
|style="text-align:center;background-color:#fff7bd;"| '''Room K'''
|style="text-align:center;background-color:#fff7bd;" | Fürstenzimmer
|style="text-align:center;background-color:#fff7bd;" | 10
|}

</div>
|}
| style="border:1px solid transparent;" |<br />
|-


{| id="mp-upper" style="width: 100%; margin:4px 0 0 0; background:none; border-spacing: 0px;"
<div id="ss1">

| class="MainPageBG" style="width:100%; border:1px solid #d6bdde; background:#f7eff7; vertical-align:top; color:#000;" |
{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:125%; font-weight:bold; border:1px solid #d6bdde; text-align:left; color:#000; padding:0.2em 0.4em;">Tutorial day</h2>
|-
| style="color:#000;" | <div id="mp-tfa" style="padding:2px 5px">
{| class="wikitable"
! style="text-align:center;background-color:#e7deef;"|
! style="text-align:center;background-color:#e7deef;"| '''Tuesday, July 5'''
|-
|style="text-align:center;background-color:#f7eff7;" | 07:30
|style="text-align:center;background-color:#f7eff7;" | Welcome coffee
|-
|style="text-align:center;background-color:#e7deef;" | 08:30
|style="text-align:center;background-color:#e7deef;" | Tutorial session
|-
|style="text-align:center;background-color:#f7eff7;" | 11:30
|style="text-align:center;background-color:#f7eff7;" | Lunch break
|-
|style="text-align:center;background-color:#e7deef;" | 12:30
|style="text-align:center;background-color:#e7deef;" | Tutorial session
|-
|style="text-align:center;background-color:#f7eff7;" | 15:30
|style="text-align:center;background-color:#f7eff7;" | Coffee break
|-
|style="text-align:center;background-color:#e7deef;" | 16:00
|style="text-align:center;background-color:#e7deef;" | Tutorial session
|-
|style="text-align:center;background-color:#f7eff7;" | 19:00
|style="text-align:center;background-color:#f7eff7;" | Welcome reception
|-
|}

Link to [[Tutorials#timetable| Tutorials schedule]].
|-
|}
| style="border:1px solid transparent;" |<br />
|-


{| id="mp-upper" style="width: 100%; margin:4px 0 0 0; background:none; border-spacing: 0px;"

| class="MainPageBG" style="width:100%; border:1px solid #bdd6c6; background:#e7f7e7; vertical-align:top; color:#000;" |
{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#d6efd6; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #bdd6c6; text-align:left; color:#000; padding:0.2em 0.4em;">Main conference</h2>
|-
| style="color:#000;" | <div id="mp-tfa" style="padding:2px 5px">
{| class="wikitable"
! style="text-align:center;background-color:#d6efd6;"|
! style="text-align:center;background-color:#d6efd6;"| '''Wednesday, July 6'''

! style="text-align:center;background-color:#d6efd6;"| '''Thursday, July 7'''

! style="text-align:center;background-color:#d6efd6;"| '''Friday, July 8'''

|-
|style="text-align:center;background-color:#e7f7e7;" | 06:30
|style="text-align:center;background-color:#e7f7e7;" | -
|style="text-align:center;background-color:#e7f7e7;" | 5K run
|style="text-align:center;background-color:#e7f7e7;" | -
|-
|style="text-align:center;background-color:#d6efd6;" | 07:30
|colspan="3" style="text-align:center;background-color:#d6efd6;"| Welcome coffee
|-
|style="text-align:center;background-color:#e7f7e7;" | 08:30
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Welcome session (Großer Saal)
|-
|style="text-align:center;background-color:#d6efd6;" | 09:00
|colspan="3" style="text-align:center;background-color:#d6efd6;"| Plenary talk
|-
|style="text-align:center;background-color:#e7f7e7;" | 10:00
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Coffee break
|-
|style="text-align:center;background-color:#d6efd6;" | 10:30
|style="text-align:center;background-color:#d6efd6;" | Session I
|style="text-align:center;background-color:#d6efd6;" | Session I
|style="text-align:center;background-color:#d6efd6;" | Session I
|-
|style="text-align:center;background-color:#e7f7e7;" | 12:10
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Lunch
|-
|style="text-align:center;background-color:#d6efd6;" | 13:10
|style="text-align:center;background-color:#d6efd6;" | Session II
|style="text-align:center;background-color:#d6efd6;" | Session II
|style="text-align:center;background-color:#d6efd6;" | Session II
|-
|style="text-align:center;background-color:#e7f7e7;" | 14:50
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Coffee break
|-
|style="text-align:center;background-color:#d6efd6;" | 15:20
|style="text-align:center;background-color:#d6efd6;" | Session III
|style="text-align:center;background-color:#d6efd6;" | Session III
|style="text-align:center;background-color:#d6efd6;" | Session III
|-
|style="text-align:center;background-color:#e7f7e7;" | 17:00
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Coffee break
|-
|style="text-align:center;background-color:#d6efd6;" | 17:30
|style="text-align:center;background-color:#d6efd6;" | -
|style="text-align:center;background-color:#d6efd6;" | Gala dinner
|style="text-align:center;background-color:#d6efd6;" | -
|-
|}

The detailed technical program can be found on the [http://edas.info/p22132 edas] website.
| style="border:1px solid transparent;" |<br />
|-

__NOTOC____NOEDITSECTION__

Schedule

2016-06-20T14:43:40Z

Hanebeck:

{| id="mp-upper" style="width: 100%; margin:4px 0 0 0; background:none; border-spacing: 0px;"

| class="MainPageBG" style="width:100%; border:1px solid #f2ea7e; background:#ffffe8; vertical-align:top; color:#000;" |
{| id="mp-left" style="width:100%; vertical-align:top; background:#ffffe8;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#fff7bd; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f2ea7e; text-align:left; color:#000; padding:0.2em 0.4em;">Room mapping</h2>
|-
| style="color:#000;" | <div id="mp-tfa" style="padding:2px 5px">
{| class="wikitable"
!style="text-align:center;background-color:#fff7bd;"| '''Room'''
! style="text-align:center;background-color:#fff7bd;"| '''Room name'''
! style="text-align:center;background-color:#fff7bd;"| '''Capacity'''
|-
|style="text-align:center;background-color:#ffffe8;"| '''A'''
|style="text-align:center;background-color:#ffffe8;" | Großer Saal
|style="text-align:center;background-color:#ffffe8;" | 1100
|-
|style="text-align:center;background-color:#fff7bd;"| '''B'''
|style="text-align:center;background-color:#fff7bd;" | Ballsaal
|style="text-align:center;background-color:#fff7bd;" | 180
|-
|style="text-align:center;background-color:#ffffe8;"| '''C'''
|style="text-align:center;background-color:#ffffe8;" | Kammermusiksaal
|style="text-align:center;background-color:#ffffe8;" | 150
|-
|style="text-align:center;background-color:#fff7bd;"| '''D'''
|style="text-align:center;background-color:#fff7bd;" | Trübnersaal
|style="text-align:center;background-color:#fff7bd;" | 104
|-
|style="text-align:center;background-color:#ffffe8;"| '''E'''
|style="text-align:center;background-color:#ffffe8;" | Sebastian-Münster-Saal
|style="text-align:center;background-color:#ffffe8;" | 80
|-
|style="text-align:center;background-color:#fff7bd;"| '''F'''
|style="text-align:center;background-color:#fff7bd;" | Gustav-Mahler-Zimmer
|style="text-align:center;background-color:#fff7bd;" | 50
|-
|style="text-align:center;background-color:#ffffe8;"| '''G'''
|style="text-align:center;background-color:#ffffe8;" | Robert-Schumann-Zimmer
|style="text-align:center;background-color:#ffffe8;" | 50
|-
|style="text-align:center;background-color:#fff7bd;"| '''H'''
|style="text-align:center;background-color:#fff7bd;" | Hölderlinsaal
|style="text-align:center;background-color:#fff7bd;" | 50
|-
|style="text-align:center;background-color:#ffffe8;"| '''I'''
|style="text-align:center;background-color:#ffffe8;" | Stefan-George-Zimmer
|style="text-align:center;background-color:#ffffe8;" | 15
|-
|style="text-align:center;background-color:#fff7bd;"| '''K'''
|style="text-align:center;background-color:#fff7bd;" | Fürstenzimmer
|style="text-align:center;background-color:#fff7bd;" | 10
|}

</div>
|}
| style="border:1px solid transparent;" |<br />
|-


{| id="mp-upper" style="width: 100%; margin:4px 0 0 0; background:none; border-spacing: 0px;"
<div id="ss1">

| class="MainPageBG" style="width:100%; border:1px solid #d6bdde; background:#f7eff7; vertical-align:top; color:#000;" |
{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:125%; font-weight:bold; border:1px solid #d6bdde; text-align:left; color:#000; padding:0.2em 0.4em;">Tutorial day</h2>
|-
| style="color:#000;" | <div id="mp-tfa" style="padding:2px 5px">
{| class="wikitable"
! style="text-align:center;background-color:#e7deef;"|
! style="text-align:center;background-color:#e7deef;"| '''Tuesday, July 5'''
|-
|style="text-align:center;background-color:#f7eff7;" | 07:30
|style="text-align:center;background-color:#f7eff7;" | Welcome coffee
|-
|style="text-align:center;background-color:#e7deef;" | 08:30
|style="text-align:center;background-color:#e7deef;" | Tutorial session
|-
|style="text-align:center;background-color:#f7eff7;" | 11:30
|style="text-align:center;background-color:#f7eff7;" | Lunch break
|-
|style="text-align:center;background-color:#e7deef;" | 12:30
|style="text-align:center;background-color:#e7deef;" | Tutorial session
|-
|style="text-align:center;background-color:#f7eff7;" | 15:30
|style="text-align:center;background-color:#f7eff7;" | Coffee break
|-
|style="text-align:center;background-color:#e7deef;" | 16:00
|style="text-align:center;background-color:#e7deef;" | Tutorial session
|-
|style="text-align:center;background-color:#f7eff7;" | 19:00
|style="text-align:center;background-color:#f7eff7;" | Welcome reception
|-
|}

Link to [[Tutorials#timetable| Tutorials schedule]].
|-
|}
| style="border:1px solid transparent;" |<br />
|-


{| id="mp-upper" style="width: 100%; margin:4px 0 0 0; background:none; border-spacing: 0px;"

| class="MainPageBG" style="width:100%; border:1px solid #bdd6c6; background:#e7f7e7; vertical-align:top; color:#000;" |
{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#d6efd6; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #bdd6c6; text-align:left; color:#000; padding:0.2em 0.4em;">Main conference</h2>
|-
| style="color:#000;" | <div id="mp-tfa" style="padding:2px 5px">
{| class="wikitable"
! style="text-align:center;background-color:#d6efd6;"|
! style="text-align:center;background-color:#d6efd6;"| '''Wednesday, July 6'''

! style="text-align:center;background-color:#d6efd6;"| '''Thursday, July 7'''

! style="text-align:center;background-color:#d6efd6;"| '''Friday, July 8'''

|-
|style="text-align:center;background-color:#e7f7e7;" | 06:30
|style="text-align:center;background-color:#e7f7e7;" | -
|style="text-align:center;background-color:#e7f7e7;" | 5K run
|style="text-align:center;background-color:#e7f7e7;" | -
|-
|style="text-align:center;background-color:#d6efd6;" | 07:30
|colspan="3" style="text-align:center;background-color:#d6efd6;"| Welcome coffee
|-
|style="text-align:center;background-color:#e7f7e7;" | 08:30
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Welcome session (Großer Saal)
|-
|style="text-align:center;background-color:#d6efd6;" | 09:00
|colspan="3" style="text-align:center;background-color:#d6efd6;"| Plenary talk
|-
|style="text-align:center;background-color:#e7f7e7;" | 10:00
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Coffee break
|-
|style="text-align:center;background-color:#d6efd6;" | 10:30
|style="text-align:center;background-color:#d6efd6;" | Session I
|style="text-align:center;background-color:#d6efd6;" | Session I
|style="text-align:center;background-color:#d6efd6;" | Session I
|-
|style="text-align:center;background-color:#e7f7e7;" | 12:10
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Lunch
|-
|style="text-align:center;background-color:#d6efd6;" | 13:10
|style="text-align:center;background-color:#d6efd6;" | Session II
|style="text-align:center;background-color:#d6efd6;" | Session II
|style="text-align:center;background-color:#d6efd6;" | Session II
|-
|style="text-align:center;background-color:#e7f7e7;" | 14:50
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Coffee break
|-
|style="text-align:center;background-color:#d6efd6;" | 15:20
|style="text-align:center;background-color:#d6efd6;" | Session III
|style="text-align:center;background-color:#d6efd6;" | Session III
|style="text-align:center;background-color:#d6efd6;" | Session III
|-
|style="text-align:center;background-color:#e7f7e7;" | 17:00
|colspan="3" style="text-align:center;background-color:#e7f7e7;"| Coffee break
|-
|style="text-align:center;background-color:#d6efd6;" | 17:30
|style="text-align:center;background-color:#d6efd6;" | -
|style="text-align:center;background-color:#d6efd6;" | Gala dinner
|style="text-align:center;background-color:#d6efd6;" | -
|-
|}

The detailed technical program can be found on the [http://edas.info/p22132 edas] website.
| style="border:1px solid transparent;" |<br />
|-

__NOTOC____NOEDITSECTION__

Venue

2016-06-18T15:05:59Z

Hanebeck:

{| id="mp-upper" style="width: 100%; margin:4px 0 0 0; background:none; border-spacing: 0px;"


| class="MainPageBG" style="width:100%; border:1px solid #bdd6c6; background:#e7f7e7; vertical-align:top; color:#000;" |
{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#d6efd6; font-family:inherit; font-size:125%; font-weight:bold; border:1px solid #bdd6c6; text-align:left; color:#000; padding:0.2em 0.4em;">Heidelberg Convention Center</h2>
|-
| style="color:#000;" | <div id="mp-tfa" style="padding:2px 5px">
The Heidelberg Convention The Kongresshaus Stadthalle Heidelberg (Heidelberg Convention Center) is centrally located and can be reached easily. Thirteen function rooms provide 2500 square meters of floor space for conventions, congresses, and events for up to 1250 people. With its sumptuous, late 19th century architecture and flashes of art nouveau brilliance, the Kongresshaus forms a stunning backdrop for conventions, congresses, balls, banquets, receptions, and concerts. While the Großer Saal (Great Hall) with its broad sweeping gallery and a capacity for 1250 persons is the jewel in the crown, smaller rooms such as the Ballsaal (Ball Room) or the Kammermusiksaal (Chamber Music Hall) are also historical gems in their own right. The Kongresshaus is nowadays equipped with the latest audio, projection, lighting, and communication technology. An in-house catering team serves international specialties, fine regional cuisine and hearty snacks.

The Kongresshaus is a house with history. It was dedicated as a gathering and festival building for the city‘s residents on the occasion of the 100th anniversary of the University Reform in 1903. Ideally situated within the Old Town, the Kongresshaus sits right on the banks of the River Neckar within the historic city of Heidelberg. Hotels, restaurants, and attractions such as the Old Bridge or the famous castle are just a few minutes away. No wonder that conventions in Heidelberg are considered “Congresses of short distances”. Directly in front of the entrance, the boats of the “Weisse Flotte” ("White Fleet") provide a really special extension area for very large gatherings. Romance meets Science – it is this mixture that makes Heidelberg such a unique venue for international and national conventions and congresses.

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<gallery mode="packed-hover">
File:Kongresshaus6_Steffen_Schmid.JPG|© Heidelberg Marketing GmbH
File:Großer_Saal2-Schmid.jpg|© Heidelberg Marketing GmbH
File:Kammermusiksaal_Sven_Hoppe-9.jpg|© Heidelberg Marketing GmbH, Photo: Sven Hoppe
File:Stadthalle_Rentsch(28).jpg|© Heidelberg Marketing GmbH
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[[File:Floorplan.png|900px|frameless|]]
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[[File:Cd0b00_d92f75fa3e9445979ac32d86a85165bd.gif|112px|Conference Catalysts, LLC|link=http://www.conferencecatalysts.com/]][[File:Blank.png|link=]][[File:Congress-and-more_logo.png|congress and morecongress and more|link=http://congressandmore.de/]]
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__NOTOC____NOEDITSECTION__

Tutorials

2016-03-02T14:36:32Z

Hanebeck:

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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
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Click [http://fusion2016.org/download/Fusion2016_CFP_Tutorials.pdf here] to download the call for tutorials.
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #d6bdde; text-align:left; color:#000; padding:0.2em 0.4em;">General Information</h2>
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The main purpose of the tutorial program is to provide overviews of the state of the art in the particular subfields of Information Fusion. This program should be useful to newcomers to the Information Fusion community to learn about the research achievements of the particular areas, as well as to currently active Information Fusion researchers who may be interested in widening their areas of research interest.

Tutorials will be held on Tuesday, July 5, 2016 from 08:30 to 19:00.
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{| id="mp-left" style="width:100%; vertical-align:top; background:#f9d6c9;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#f5baa3; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f36766; text-align:left; color:#000; padding:0.2em 0.4em;">Information for Tutorial Attendees</h2>
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* Please select up to three tutorials, one from each time slot.
* The tutorials are assigned fixed numbers (T1 to T26) that will not be changed in the event of cancellations.
* During registration, please select the desired tutorials (by number or name).
* There will be a discount for booking two or three tutorials, see [[Fees and Registration| Fees and Registration page]].
* You will obtain printed coupons for your tutorials while checking in for the conference. These coupons contain your name and the name of the selected tutorials and are required for participation.
* In the unlikely event that tutorials get canceled, we will offer alternatives to you. Of course, you can always opt for a refund if your chosen tutorials do not take place.
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"

| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#ceecf2; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3babf; text-align:left; color:#000; padding:0.2em 0.4em;">Information for Tutorial Presenters</h2>
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* The conference does not offer any printing services and is not responsible for study materials distributed to the attendees. This is solely the responsibility of the presenter.
* There will be an honorarium for tutorial presenters, which is made up of a basic amount plus a variable bonus. The bonus is directly taken from the tutorial fees and thus proportional to the number of attendees. When there is more than one presenter, the honorarium is paid to the first person named in the program.
* The number of attendees will be counted based on the registrations.
* When less than 5 people register, the tutorial will be canceled.
* Please be present in your assigned room early. The time and room for your tutorial is shown in the [[Tutorials#timetable| time table]] below.
* There will be a technician and a student volunteer helping you with setting up the system and providing access control.
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{| id="mp-left" style="width:100%; vertical-align:top; background:#ffffe8;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#fff7bd; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f2ea7e; text-align:left; color:#000; padding:0.2em 0.4em;">List of Tutorials of FUSION 2016</h2>
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* [[Tutorials#tutorial1| T1 Bayesian Multiple Target Tracking]]
* [[Tutorials#tutorial2| T2 Bayesian Networks and Trust Fusion with Subjective Logic]]
* [[Tutorials#tutorial3| T3 Multisensor-Multitarget Tracker/Fusion Engine Development and Performance Evaluation for Realistic Scenarios]]
* [[Tutorials#tutorial4| T4 An Introduction to Track-to-Track Fusion and the Distributed Kalman Filter]]
* [[Tutorials#tutorial5| T5 An Introduction to Finite-Set Statistics for Information Fusion]]
* [[Tutorials#tutorial6| T6 Information Quality in Information Fusion and Decision Making]]
* [[Tutorials#tutorial7| T7 Multitarget Tracking and Multisensor Information Fusion]]
* [[Tutorials#tutorial8| T8 Overview of High-Level Information Fusion Theory, Models, and Representations]]
* [[Tutorials#tutorial9| T9 Quantum Physics Methods for Nonlinear Filtering]]
* [[Tutorials#tutorial10| T10 Basic Concepts in Multiobject Estimation]]
* [[Tutorials#tutorial11| T11 System-of-Systems Concepts, Opportunities and Issues for Information Fusion]]
* [[Tutorials#tutorial12| T12 Implementations of Random-Finite-Set-Based Multi-Target Filters]]
* [[Tutorials#tutorial13| T13 Tracking and Sensor Data Fusion – Methodological Framework and Selected Applications]]
* [[Tutorials#tutorial14| T14 Multistatic Exploration – Introduction to Modern Passive Radar and Multistatic Tracking & Data Fusion]]
* [[Tutorials#tutorial15| T15 Big Data Fusion and Analytics]]
* [[Tutorials#tutorial16| T16 Object Tracking, Sensor Fusion and Situational Awareness for Assisted- and Self-Driving Vehicles: Problems, Solutions and Directions]]
* [[Tutorials#tutorial17| T17 Emerging Quantum Technologies for Fusion]]
* [[Tutorials#tutorial18| T18 Maneuvering Target Tracking: Overview and Nonlinear Filtering Methods]]
* [[Tutorials#tutorial19| T19 Integration of Information to Indentify Objects in Big Data]]
* [[Tutorials#tutorial20| T20 Extended Object Tracking: Theory and Applications]]
* [[Tutorials#tutorial21| T21 Probabilistic Situation Assessment for Abnormal Interaction Detection]]
* [[Tutorials#tutorial22| T22 Multitarget Tracking and Sensor Calibration in Centralized and Distributed Networks]]
* [[Tutorials#tutorial23| T23 Information Fusion in Resource-Limited Camera Networks]]
* [[Tutorials#tutorial24| T24 Introduction to Bayesian Filtering and Smoothing]]
* [[Tutorials#tutorial25| T25 Sensor Fusion for Intelligent Vehicles]]
* [[Tutorials#tutorial26| T26 Multisensor Data Fusion in Wireless Sensor and Actuator Networks]]

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<div id="timetable"></div>
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #d6bdde; text-align:left; color:#000; padding:0.2em 0.4em;">Time Table for the Tutorials Day on Tuesday, July 5, 2016</h2>
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{| class="wikitable" style="text-align:center;background-color:#e7deef;"
! style="width:8em;text-align:center;background-color:#e7deef;"|'''Start & end times'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 1'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 2'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 3'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 4'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 5'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 6'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 7'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 8'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 9'''
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|style="text-align:center;background-color:#e7deef;" | '''Morning'''<br />
'''08:30 - 11:30'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial1| T1]]'''<br />
Bayesian Multiple Target Tracking<br />
''Stone, Streit''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial2| T2]]'''<br />
Bayesian Networks and Trust Fusion with Subjective Logic<br />
''Jøsang''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial3| T3]]'''<br />
Multisensor-Multitarget Tracker/Fusion Engine …<br />
''Kiruba''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial4| T4]]'''<br />
… Track-to-Track Fusion and the Distributed Kalman Filter<br />
''Govaers''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial15| T15]]'''<br />
Big Data Fusion and Analytics<br />
''Das''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial14| T14]]'''<br />
Multistatic Exploration ... Modern Passive Radar …<br />
''Koch''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial7| T7]]'''<br />
Multitarget Tracking and Multisensor Information Fusion<br />
''Bar-Shalom''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial8| T8]]'''<br />
Overview of High-Level Information Fusion Theory …<br />
''Blasch''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial9| T9]]'''<br />
Quantum Physics Methods For Nonlinear Filtering<br />
''Balaji, Daum''
|-
|style="width:7em;text-align:center;background-color:#e7deef;"| '''11:30-12:30'''
|colspan="9" style="width:15em;text-align:center;background-color:#f7eff7;"|
'''Lunch break'''<br />

|-
|style="text-align:center;background-color:#e7deef;" | '''Mid Day'''
'''12:30-15:30'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial10| T10]]'''<br />
Basic concepts in multi-object estimation<br />
''Clark, Delande, Houssineau''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutoria11| T11]]'''<br />
System-of-Systems … Issues for Information Fusion<br />
''Steinberg''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial12| T12]]'''<br />
... random-finite-set-based multi-target filters<br />
''Vo, Vo''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial13| T13]]'''<br />
Tracking and Sensor Data Fusion ... Framework …<br />
''Koch''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial6| T6]]'''<br />
Information Quality in Information Fusion …<br />
''Rogova''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial23| T23]]'''<br />
Information fusion in resource-limited camera networks<br />
''Cavallaro, SanMiguel''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial16| T16]]'''<br />
Object tracking, sensor fusion ... self-driving vehicles …<br />
''Kiruba''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial17| T17]]'''<br />
Emerging Quantum Technologies for Fusion<br />
''Balaji''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial18| T18A]]'''<br />
Maneuvering Target Tracking ... Filtering Methods<br />
''Li, Jilkov''
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|style="width:7em;text-align:center;background-color:#e7deef;"| '''15:30-16:00'''
|colspan="9" style="width:15em;text-align:center;background-color:#f7eff7;"|
'''Coffee/tea break'''<br />

|-
|style="text-align:center;background-color:#e7deef;" | '''Afternoon'''<br />
'''16:00-19:00'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial18| T18B]]'''<br />
Maneuvering Target Tracking ... Filtering Methods<br />
''Li, Jilkov''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutoria19| T19]]'''<br />
Integration of Information to Identify Objects in Big Data<br />
''Shieh''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial20| T20]]'''<br />
Extended Object Tracking: Theory and Applications<br />
''Granström, Reuter, Baum''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial21| T21]]'''<br />
Probabilistic situation assessment for abnormal …<br />
''Regazzoni, Marcenaro''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial22| T22]]'''<br />
Multitarget tracking and sensor calibration in ... networks<br />
''Uney, Julier, Clark''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial5| T5]]'''<br />
... Finite-Set Statistics for Information Fusion<br />
''Mahler''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial24| T24]]'''<br />
Introduction to Bayesian Filtering and Smoothing<br />
''Särkkä''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial25| T25]]'''<br />
Sensor Fusion for Intelligent Vehicles<br />
''Duraisamy, Yuan, Schwarz, Fritzsche''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial26| T26]]'''<br />
Multisensor Data Fusion in Wireless ... Networks<br />
''Miceli de Farias''
|-
|style="width:7em;text-align:center;background-color:#e7deef;"| '''19:00-22:00'''
|colspan="9" style="width:15em;text-align:center;background-color:#f7eff7;"|
'''Welcome Reception'''<br />

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{| id="mp-left" style="width:100%; vertical-align:top; background:#f9d6c9;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#f5baa3; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f36766; text-align:left; color:#000; padding:0.2em 0.4em;">T1 Bayesian Multiple Target Tracking</h2>
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'''Presenter:''' [mailto:stone@metsci.com Lawrence D. Stone] and Roy L. Streit<br />
'''Length:''' 3 hours<br />
'''Brief description:''' This tutorial is based on the book, Bayesian Multiple Target Tracking 2nd Ed. Its purpose is to present the basic results in multiple-target tracking from a Bayesian point of view. People who register will receive a complimentary copy of the book when they attend the tutorial.<br />
[[T1| More Details]]
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<div id="tutorial2"></div>

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| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#ceecf2; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3babf; text-align:left; color:#000; padding:0.2em 0.4em;">T2 Bayesian Networks and Trust Fusion with Subjective Logic</h2>
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'''Presenter:''' [mailto:audun.josang@mn.uio.no Audun Jøsang]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' This tutorial gives attendees a first-hand insight into the theory and application of subjective logic by the author and researcher who proposed and started developing this framework in 1997. The tutorial gives an introduction to subjective logic, and how it applies to Bayesian network modelling and information fusion. ...<br />
[[T2| More Details]]
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#d6efd6; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #bdd6c6; text-align:left; color:#000; padding:0.2em 0.4em;">T3 Multisensor-Multitarget Tracker/Fusion Engine Development and Performance Evaluation for Realistic Scenarios</h2>
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'''Presenter:''' [mailto:kiruba@mcmaster.ca T. Kirubarajan]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' While numerous tracking and fusion algorithms are available in the literature, their implementation and application on real-world problems are still challenging. Since new algorithms continue to emerge, rapidly prototyping them, developing for production and evaluating them on real-world (or realistic) problems efficiently are also essential. In addition to reviewing state-of-the-art tracking algorithms, this tutorial will focus on a number of realistic multisensor-multitarget tracking problems, simulation of large-scale tracking scenarios, rapid prototyping, development of high performance real-time tracking/fusion software, and performance evaluation on realistic scenarios. ...<br />
[[T3| More Details]]
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{| id="mp-left" style="width:100%; vertical-align:top; background:#ffffe8;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#fff7bd; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f2ea7e; text-align:left; color:#000; padding:0.2em 0.4em;">T4 An Introduction to Track-to-Track Fusion and the Distributed Kalman Filter</h2>
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'''Presenter:''' [mailto:felix.govaers@fkie.fraunhofer.de Felix Govaers]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' The increasing trend towards connected sensors (”internet of things” and ”ubiquitous computing”) derive a demand for powerful distributed estimation methodologies. In tracking applications, the ”Distributed Kalman Filter” (DKF) provides an optimal solution under certain conditions. The optimal solution in terms of the estimation accuracy is also achieved by a centralized fusion algorithm which receives either all associated measurements or so-called tracklets.... Two more recent methodologies are based on the ”accumulated state densities” (ASD) which augment the states from multiple time instants. In practical applications, tracklet fusion based on the equivalent measurement often achieves reliable results even if full communication is not available. The limitations and robustness of the tracklet fusion will be discussed. ...<br />
[[T4| More Details]]
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #d6bdde; text-align:left; color:#000; padding:0.2em 0.4em;">T5 An Introduction to Finite-Set Statistics for Information Fusion</h2>
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'''Presenter:''' [mailto:mahlerronald@comcast.net Ronald Mahler]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' Finite-set statistics is a theoretically unified mathematical machine for solving information fusion problems, based on random set theory. First systematically described in Statistical Multisource-Multitarget Information Fusion (Artech, 2007), it has attracted the interest of dozens of research groups in at least 19 nations, resulting in well over a thousand publications. Advances in Statistical Multisource-Multitarget Information Fusion (Artech, 2014) systematically described the most intriguing aspects of this research, including algorithms that outperform conventional approaches. Previous tutorials have focused on applications of random set information fusion. This is the first systematic tutorial treatment of finite-set statistics itself. ...<br />
[[T5| More Details]]
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<div id="tutorial6">

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{| id="mp-left" style="width:100%; vertical-align:top; background:#f9d6c9;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#f5baa3; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f36766; text-align:left; color:#000; padding:0.2em 0.4em;">T6 Information Quality in Information Fusion and Decision Making</h2>
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'''Presenter:''' [mailto:rogovagl@gmail.com Galina Rogova]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' ... The tutorial will discuss major challenges and some possible approaches addressing the problem of representing and incorporating information quality into fusion processes. In particular it will present an ontology of quality of information and identify potential methods of representing and assessing the values of quality attributes and their combination. It will also examine the relation between information quality and context, and suggest possible approaches to quality control compensating for insufficient information and model quality.<br />
[[T6| More Details]]
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<div id="tutorial7"></div>

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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"

| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#ceecf2; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3babf; text-align:left; color:#000; padding:0.2em 0.4em;">T7 Multitarget Tracking and Multisensor Information Fusion</h2>
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'''Presenter:''' [mailto:ybs@engr.uconn.edu Yaakov Bar-Shalom]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' To provide to the participants the latest state-of-the art techniques to estimate the states ofmultiple targets with multisensor information fusion. Tools for algorithm selection, design and evaluation willbe presented. These form the basis of automated decision systems foradvanced surveillanceandtargeting.The various information processing configurations for fusion are described, including the recently solvedtrack-to-track fusion from heterogeneous sensors.<br />
[[T7| More Details]]
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{| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;"
<div id="tutorial8"></div>

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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#d6efd6; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #bdd6c6; text-align:left; color:#000; padding:0.2em 0.4em;">T8 Overview of High-Level Information Fusion Theory, Models, and Representations</h2>
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'''Presenter:''' [mailto:erik.blasch@gmail.com Erik Blasch]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' Over the past decade, the ISIF community has put together special sessions, panel discussions, and concept papers to capture the methodologies, directions, needs, and grand challenges of high-level information fusion (HLIF) in practical system designs. This tutorial brings together the contemporary concepts, models, and definitions to give the attendee a summary of the state-of-the-art in HLIF. Analogies from low-level information fusion (LLIF) of object tracking and identification are extended to the HLIF concepts of situation/impact assessment and process/user refinement. HLIF theories (operational, functional, formal, cognitive) are mapped to representations (semantics, ontologies, axiomatics, and agents) with contemporary issues of modeling, testbeds, evaluation, and human-machine interfaces. Discussions with examples of search and rescue, cyber analysis, and battlefield awareness are presented. ...<br />
[[T8| More Details]]
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<div id="tutorial9"></div>

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{| id="mp-left" style="width:100%; vertical-align:top; background:#ffffe8;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#fff7bd; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f2ea7e; text-align:left; color:#000; padding:0.2em 0.4em;">T9 Quantum Physics Methods for Nonlinear Filtering</h2>
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'''Presenter:''' [mailto:Bhashyam.Balaji@drdc-rddc.gc.ca Bhashyam Balaji] and [mailto:Frederick_E_Daum@raytheon.com Fred Daum]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' Relationships between nonlinear filtering and quantum physics has been studied in the past. In this tutorial, more modern connections between the two fields are drawn, particularly based on methods drawn from Feynman path integrals, quantum field theory and renormalization group.<br />
[[T9| More Details]]
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<div id="tutorial10"></div>

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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #d6bdde; text-align:left; color:#000; padding:0.2em 0.4em;">T10 Basic Concepts in Multiobject Estimation</h2>
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'''Presenter:''' [mailto:D.E.Clark@hw.ac.uk Daniel Clark], Emmanuel D. Delande, and Jérémie Houssineau<br />
'''Length:''' 3 hours<br />
'''Brief description:''' ... This tutorial will highlight some basic mathematical concepts in multiobject estimation to enable researchers to better understand and contribute to innovations in this field. The goal of the presenters is to inspire participants to develop a broader mathematical perspective and explore the literature in spatial statistics and point processes to aid their research in sensor fusion. The presenters will highlight where new concepts to multiobject estimation in sensor fusion, such as regional variance for estimating population uncertainty, can be facilitated when considering a measuretheoretic point process perspective.<br />
[[T10| More Details]]
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{| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;"
<div id="tutorial11">

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{| id="mp-left" style="width:100%; vertical-align:top; background:#f9d6c9;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#f5baa3; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f36766; text-align:left; color:#000; padding:0.2em 0.4em;">T11 System-of-Systems Concepts, Opportunities and Issues for Information Fusion</h2>
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'''Presenter:''' [mailto:alaneilsteinberg@gmail.com Alan Steinberg]<br />
'''Length:''' 3 hours <br />
'''Brief description:''' Current concepts and methods in System-of-Systems Engineering (SoSE) will be presented, together with the role of information fusion. ... Methods for maximizing the effectiveness of cooperative sensing and cooperative engagement tactics will be discussed. ... Advanced multi-sensor, highly integrated weapons platforms provide enormous new capabilities. ... Data integrity and consistency are critical in integrating and using systems-of-systems. Attendees will learn current techniques for aligning data in space and time and in confidence. ... There will be discussion of SoS Engineering methodology for developing SoS architectural and management solutions to meet requirements of technical performance, cost, flexibility and extensibility. Developmental and operational testing and evaluation of systems-of-systems involves special challenges, not the least of which are multiple interacting control-loops in such systems.<br />
[[T11| More Details]]
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{| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;"
<div id="tutorial12"></div>

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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"

| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#ceecf2; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3babf; text-align:left; color:#000; padding:0.2em 0.4em;">T12 Implementations of Random-Finite-Set-Based Multi-Target Filters</h2>
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'''Presenter:''' [mailto:ba-ngu.vo@curtin.edu.au Ba-Ngu Vo] and Ba-Tuong Vo<br />
'''Length:''' 3 hours<br />
'''Brief description:''' The Finite Set Statistics framework for multi-sensor multi-target tracking has attached considerable interest in recent years. It provides a unified perspective of multi-target tracking in a very intuitive manner by drawing direct parallels with the simpler problem of single-target tracking. This framework has lead to the development of multi-target filters such as the Probability Hypothesis Density (PHD), Cardinalized PHD (CPHD), Multi-Bernoulli filters and recently, the Generalized Labeled Multi-Bernoulli filter. In this tutorial, we show how these filters are implemented and illustrate via Matlab how these filters work. ...<br />
[[T12| More Details]]
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{| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;"
<div id="tutorial13"></div>

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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#d6efd6; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #bdd6c6; text-align:left; color:#000; padding:0.2em 0.4em;">T13 Tracking and Sensor Data Fusion – Methodological Framework and Selected Applications</h2>
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'''Presenter:''' [mailto:wolfgang.koch@fkie.fraunhofer.de Wolfgang Koch]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' The tutorial covers the material of the recently published book of the presenter with the same title (Springer 2014, Mathematical Engineering Series, ISBN 978-3-642-39270-2) and thus provides an guided introduction to deeper reading. Starting point is the well known JDL model of sensor data and information fusion that provides general orientation within the world of fusion methodologies and its various applications, covering a dynamically evolving field of ever increasing relevance. Using the JDL model as a guiding principle, the tutorial introduces into advanced fusion technologies based on practical examples taken from real world applications.<br />
[[T13| More Details]]
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{| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;"
<div id="tutorial14"></div>

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{| id="mp-left" style="width:100%; vertical-align:top; background:#ffffe8;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#fff7bd; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f2ea7e; text-align:left; color:#000; padding:0.2em 0.4em;">T14 Multistatic Exploration – Introduction to Modern Passive Radar and Multistatic Tracking & Data Fusion</h2>
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'''Presenter:''' [mailto:wolfgang.koch@fkie.fraunhofer.de Wolfgang Koch]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' Advanced distributed signal and data fusion for passive radar systems, where DVB TV or GSM mobile phone base stations are used as sources for illuminating targets, for example, is a topic of increasing interest. Even in remote regions of the world, transmitters of electromagnetic radiation become a potential radar transmitter stations enabling covert surveillance for air, sea, and ground scenarios. Analogous considerations are valid for sub-sea surveillance. Illustrated by examples and experimental results, principles of passive radar as well as advanced multistatic tracking and de-ghosting techniques will be discussed.<br />
[[T14| More Details]]
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<div id="tutorial15"></div>

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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #d6bdde; text-align:left; color:#000; padding:0.2em 0.4em;">T15 Big Data Fusion and Analytics</h2>
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'''Presenter:''' [mailto:sdas@machineanalytics.com Subrata Das]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' Big data has tremendous potential to transform businesses but poses significant challenge in searching, processing, and extracting actionable intelligence. In this tutorial, I will present some techniques for fusion and analytics to process big centralized warehouse data, inherently distributed data, and data residing on the cloud. The fusion and analytics techniques to be discussed will handle both structured transactional and sensor data as well as unstructured textual data such as human intelligence, emails, blogs, surveys, etc. As a background, this tutorial is intended to provide an account of both the cutting-edge and the most commonly used approaches to high-level data fusion and predictive and text analytics. The demos to be presented are in the areas of distributed search and situation assessment, information extraction and classification, and sentiment analyses. ...<br />
[[T15| More Details]]
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<div id="tutorial16">

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{| id="mp-left" style="width:100%; vertical-align:top; background:#f9d6c9;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#f5baa3; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f36766; text-align:left; color:#000; padding:0.2em 0.4em;">T16 Object Tracking, Sensor Fusion and Situational Awareness for Assisted- and Self-Driving Vehicles: Problems, Solutions and Directions</h2>
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'''Presenter:''' [mailto:kiruba@mcmaster.ca T. Kirubarajan]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' ... In this tutorial, we aim to discuss a number of problems related to assisted- and self-driving vehicles, potential solutions and directions for research & development. The issues discussed in this tutorial will span multitarget tracking, multisensor fusion and situational awareness within the context of smart cars. We will also present some of the algorithms that are available in the open literature as well as those we have developed recently. In addition, we will also discuss related computational issues and sensor technologies. Finally, we will present some results on real data.<br />
[[T16| More Details]]
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<div id="tutorial17"></div>

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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"

| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#ceecf2; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3babf; text-align:left; color:#000; padding:0.2em 0.4em;">T17 Emerging Quantum Technologies for Fusion</h2>
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'''Presenter:''' [mailto:Bhashyam.Balaji@drdc-rddc.gc.ca Bhashyam Balaji]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' ... Although the fundamentals of quantum physics have been well-known since the 1920s, in the last few decades several novel consequences of the laws of quantum physics (particularly, in the areas of atomic, molecular and optical physics and quantum computer science and information theory) have been discovered. ... In particular, in the areas of sensing, quantum physics sets the bounds on the sensitivity of sensing... that is orders of magnitude below the sensitivity of current sensors. In the area of computing, it has been observed that a quantum computer allows some computations to be carried out that are unfeasible using current or future classical computing technology. In the area of communication, quantum physics enables provable secure communication and at much higher data rates than those allowed by classical Shannon limit. Many of these advances could have major near-term and long-term consequences in the areas of sensing, secure communication, big data analysis, and machine learning, and hence sensor and information fusion.<br />
[[T17| More Details]]
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<div id="tutorial18"></div>

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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#d6efd6; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #bdd6c6; text-align:left; color:#000; padding:0.2em 0.4em;">T18 Maneuvering Target Tracking: Overview and Nonlinear Filtering Methods</h2>
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'''Presenter:''' [mailto:XLi@uno.edu X. Rong Li] and [mailto:vjilkov@uno.edu Vesselin P. Jilkov]<br />
'''Length:''' 3+3 hours<br />
'''Brief description:''' The principal challenges for tracking a maneuverable target are nonlinearity in both target motion and measurement models as well as the uncertainty in the pattern of target motion. This tutorial presents theoretical and algorithmic means available to meet these challenges. The overview part elucidates a well organized panorama of maneuvering target tracking. The other part presents an in-depth coverage of recent advances in nonlinear filtering for maneuvering target tracking, including some of the instructors’ results and insights as well as better known methods. The tutorial highlights the underlying ideas and pros and cons of approaches and techniques as well as inter-relationships among them. It is an outgrowth of the instructors’ ongoing comprehensive survey and several short courses of the same subject as well as a graduate course on target tracking taught at the Electrical Engineering Department of the University of New Orleans.<br />
[[T18| More Details]]
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<div id="tutorial19"></div>

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{| id="mp-left" style="width:100%; vertical-align:top; background:#ffffe8;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#fff7bd; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f2ea7e; text-align:left; color:#000; padding:0.2em 0.4em;">T19 Integration of Information to Identify Objects in Big Data</h2>
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'''Presenter:''' [mailto:gshieh@webmail.stat.sinica.edu.tw Grace S. Shieh]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' Big data has tremendous potential to transform businesses and research but raises significant challenges in pre-processing and extracting useful information and information integration to identify objects of interest. In this tutorial, I will present some statistical methods/machine learning for fusion and analysis of big data in cancer research, e.g., DNA sequencing data, gene expression data (RNA-seq) from The Cancer Genome Atlas (TCGA), protein expression and clinical features of cancer patients. This tutorial aims to cover both useful statistical/data mining methods and the cutting-edge directions. ...<br />
[[T19| More Details]]
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #d6bdde; text-align:left; color:#000; padding:0.2em 0.4em;">T20 Extended Object Tracking: Theory and Applications</h2>
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'''Presenter:''' [mailto:karl.granstrom@chalmers.se Karl Granström], Stephan Reuter, and [mailto:marcus.baum@cs.uni-goettinge.de Marcus Baum]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' Autonomous driver safety functions are standard in many modern cars, and semi-automated systems (e.g., traffic jam assist) are becoming more and more common. Construction of a driverless vehicle requires solutions to many different problems, among them multiple object tracking. This tutorial will introduce the audience to extended object tracking, i.e., object tracking using modern high resolution sensors that give multiple detections per object. State of the art theory will be introduced, and relevant real world applications will be shown where different object types—e.g., pedestrians, bicyclists, cars—are tracked using different sensors such as lidar, radar, and camera.<br />
[[T20| More Details]]
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<div id="tutorial21">

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{| id="mp-left" style="width:100%; vertical-align:top; background:#f9d6c9;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#f5baa3; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f36766; text-align:left; color:#000; padding:0.2em 0.4em;">T21 Probabilistic Situation Assessment for Abnormal Interaction Detection</h2>
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'''Presenter:''' [mailto:carlo.regazzoni@unige.it Carlo Regazzoni] and [mailto:lucio.marcenaro@unige.it Lucio Marcenaro]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' The tutorial aims at providing an overview of new insights in extending Dynamic Bayesian Networks techniques for representing, modeling and automatically interpreting and managing complex interaction situations occurring in cognitive environments starting from observations provided by multidimensional signals collected through a distributed network of embedded systems. A uniform representation is discussed that can also be used to support decisions concerning interactions between operators and the status of the observed environment. Solutions, which are based on an extension of traditional Bayesian filters for object assessment, are the basis background of discussion from which techniques in this tutorial. ...<br />
[[T21| More Details]]
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<div id="tutorial22"></div>

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| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#ceecf2; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3babf; text-align:left; color:#000; padding:0.2em 0.4em;">T22 Multitarget Tracking and Sensor Calibration in Centralized and Distributed Networks</h2>
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'''Presenter:''' Murat Uney, Simon Julier, and [mailto:D.E.Clark@hw.ac.uk Daniel Clark]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' … This tutorial will present methods for fusion and registration in networks of sensors. In the first part, the focus will be on integrating information output by local filtering at the sensor nodes. Both optimal and suboptimal algorithms will be presented and discussed. The second part will cover registration/calibration of sensors. First, a centralised setting will be considered in which the sensor measurements are available at a centre. It will be shown how the registration process can exploit the Probability Hypothesis Density (PHD) filtering principles for handling the uncertainties in the multitarget model. The second topic will be a distributed setting in which several sensor nodes exchange filtered distributions as opposed to measurements. A recent solution will be introduced which feature local processing at the sensor nodes and message passing operations for selfcalibration.<br />
[[T22| More Details]]
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#d6efd6; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #bdd6c6; text-align:left; color:#000; padding:0.2em 0.4em;">T23 Information Fusion in Resource-Limited Camera Networks</h2>
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'''Presenter:''' [mailto:a.cavallaro@qmul.ac.uk Andrea Cavallaro] and [mailto:juancarlos.sanmiguel@uam.es Juan C. SanMiguel]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' … This tutorial will introduce key features of modern visual sensor networks while exploring the issues commonly found in such networks, which have recently become central in several applications. For smart-camera networks to enable these emerging applications they need to adapt to unforeseen conditions and varying tasks under constrained resources. The tutorial will offer theoretical explanations followed by examples using the WiseMNet++ simulator.<br />
[[T23| More Details]]
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{| id="mp-left" style="width:100%; vertical-align:top; background:#ffffe8;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#fff7bd; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f2ea7e; text-align:left; color:#000; padding:0.2em 0.4em;">T24 Introduction to Bayesian Filtering and Smoothing</h2>
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'''Presenter:''' [mailto:simo.sarkka@aalto.fi Simo Särkkä]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' ... The tutorial introduces the current state-of-the-art of non-linear (single-target) optimal filtering and smoothing methods in a unified Bayesian framework. The attendees learn what non-linear Kalman filters and particle filters are, how they are related, and their relative advantages and disadvantages. They also discover how Bayesian parameter estimation methods can be combined with the filtering and smoothing algorithms. ... Example applications from navigation, remote surveillance, and time series analysis.<br />
[[T24| More Details]]
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
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'''Presenter:''' [mailto:bharanid-har.duraisamy@daimler.com Bharanidhar Duraisamy], [mailto:ting.yuan@daimler.com Ting Yuan], [mailto:tilo.schwarz@daimler.com Tilo Schwarz], and [mailto:martin.fritzsche@daimler.com Martin Fritzsche]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' This tutorial is focussed towards the stringent requirements, foundations, development and testing of sensor fusion algorithms meant for advanced driver assistance functions and driverless applications in automotive vehicle systems. ... The interesting part of the tutorial is covered on the different challenging and important practical aspects such as fusion with incomplete information, data association, etc. related to fusion and target tracking in automotive setting. Fusion and management of the different extended target representations of heterogeneous nature obtained from sensors with different resolution is presented with examples. More than one kind of intelligent vehicular sensor fusion framework dealing with tracked objects i.e. track level fusion and raw sensor measurements i.e. measurement level fusion, with results obtained using several real world data sets that contains various static and dynamic targets would be presented in this tutorial.<br />
[[T25| More Details]]
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{| id="mp-left" style="width:100%; vertical-align:top; background:#f9d6c9;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#f5baa3; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f36766; text-align:left; color:#000; padding:0.2em 0.4em;">T26 Multisensor Data Fusion in Wireless Sensor and Actuator Networks</h2>
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'''Presenter:''' [mailto:cmicelifarias@gmail.com Claudio Miceli de Farias]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' This tutorial focuses on presenting Multisensor Data Fusion Techniques for Wireless Sensor and Actuator networks. Advances in microelectromechanical systems technologies and wireless communications have enabled the construction of devices, called sensors, endowed with processing and communication capabilities, used to monitor physical quantities in an environment. ... Recent years have witnessed the emergence of the Shared/ Virtual Sensor and Actuator Networks, which instead of assuming an application-specific design, allow the sensing and communication infrastructure to be shared among multiple applications. ... However, wireless sensors and actuators commonly rely on batteries as their energy sources, whose replacement is undesirable or unfeasible. Therefore, in order to reduce the amount of data to be transmitted in the wireless channel, thus saving energy, Multisensor Data Fusion Methods (MDF) can be employed.<br />
[[T26| More Details]]
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[[File:Cd0b00_d92f75fa3e9445979ac32d86a85165bd.gif|120px|Conference Catalysts, LLC|link=http://www.conferencecatalysts.com/]][[File:Congress-and-more_logo.png|congress and morecongress and more|link=http://congressandmore.de/]]
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__NOTOC____NOEDITSECTION__

Tutorials

2016-02-29T16:35:47Z

Hanebeck:

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Click [http://fusion2016.org/download/Fusion2016_CFP_Tutorials.pdf here] to download the call for tutorials.
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The main purpose of the tutorial program is to provide overviews of the state of the art in the particular subfields of Information Fusion. This program should be useful to newcomers to the Information Fusion community to learn about the research achievements of the particular areas, as well as to currently active Information Fusion researchers who may be interested in widening their areas of research interest.

Tutorials will be held on Tuesday, July 5, 2016 from 08:30 to 19:00.
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* Please select up to three tutorials, one from each time slot.
* The tutorials are assigned fixed numbers (T1 to T26) that will not be changed in the event of cancellations.
* During registration, please select the desired tutorials (by number or name).
* There will be a discount for booking two or three tutorials, see [[Fees and Registration| Fees and Registration page]].
* You will obtain printed coupons for your tutorials while checking in for the conference. These coupons contain your name and the name of the selected tutorials and are required for participation.
* In the unlikely event that tutorials get canceled, we will offer alternatives to you. Of course, you can always opt for a refund if your chosen tutorials do not take place.
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| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#ceecf2; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3babf; text-align:left; color:#000; padding:0.2em 0.4em;">Information for Tutorial Presenters</h2>
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* The conference does not offer any printing services and is not responsible for study materials distributed to the attendees. This is solely the responsibility of the presenter.
* There will be an honorarium for tutorial presenters, which is made up of a basic amount plus a variable bonus. The bonus is directly taken from the tutorial fees and thus proportional to the number of attendees. When there is more than one presenter, the honorarium is paid to the first person named in the program.
* The number of attendees will be counted based on the registrations.
* When less than 4 people register, the tutorial will be canceled.
* Please be present in your assigned room early. The time and room for your tutorial is shown in the [[Tutorials#timetable| time table]] below.
* There will be a technician and a student volunteer helping you with setting up the system and providing access control.
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{| id="mp-left" style="width:100%; vertical-align:top; background:#ffffe8;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#fff7bd; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f2ea7e; text-align:left; color:#000; padding:0.2em 0.4em;">List of Tutorials of FUSION 2016</h2>
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* [[Tutorials#tutorial1| T1 Bayesian Multiple Target Tracking]]
* [[Tutorials#tutorial2| T2 Bayesian Networks and Trust Fusion with Subjective Logic]]
* [[Tutorials#tutorial3| T3 Multisensor-Multitarget Tracker/Fusion Engine Development and Performance Evaluation for Realistic Scenarios]]
* [[Tutorials#tutorial4| T4 An Introduction to Track-to-Track Fusion and the Distributed Kalman Filter]]
* [[Tutorials#tutorial5| T5 An Introduction to Finite-Set Statistics for Information Fusion]]
* [[Tutorials#tutorial6| T6 Information Quality in Information Fusion and Decision Making]]
* [[Tutorials#tutorial7| T7 Multitarget Tracking and Multisensor Information Fusion]]
* [[Tutorials#tutorial8| T8 Overview of High-Level Information Fusion Theory, Models, and Representations]]
* [[Tutorials#tutorial9| T9 Quantum Physics Methods for Nonlinear Filtering]]
* [[Tutorials#tutorial10| T10 Basic Concepts in Multiobject Estimation]]
* [[Tutorials#tutorial11| T11 System-of-Systems Concepts, Opportunities and Issues for Information Fusion]]
* [[Tutorials#tutorial12| T12 Implementations of Random-Finite-Set-Based Multi-Target Filters]]
* [[Tutorials#tutorial13| T13 Tracking and Sensor Data Fusion – Methodological Framework and Selected Applications]]
* [[Tutorials#tutorial14| T14 Multistatic Exploration – Introduction to Modern Passive Radar and Multistatic Tracking & Data Fusion]]
* [[Tutorials#tutorial15| T15 Big Data Fusion and Analytics]]
* [[Tutorials#tutorial16| T16 Object Tracking, Sensor Fusion and Situational Awareness for Assisted- and Self-Driving Vehicles: Problems, Solutions and Directions]]
* [[Tutorials#tutorial17| T17 Emerging Quantum Technologies for Fusion]]
* [[Tutorials#tutorial18| T18 Maneuvering Target Tracking: Overview and Nonlinear Filtering Methods]]
* [[Tutorials#tutorial19| T19 Integration of Information to Indentify Objects in Big Data]]
* [[Tutorials#tutorial20| T20 Extended Object Tracking: Theory and Applications]]
* [[Tutorials#tutorial21| T21 Probabilistic Situation Assessment for Abnormal Interaction Detection]]
* [[Tutorials#tutorial22| T22 Multitarget Tracking and Sensor Calibration in Centralized and Distributed Networks]]
* [[Tutorials#tutorial23| T23 Information Fusion in Resource-Limited Camera Networks]]
* [[Tutorials#tutorial24| T24 Introduction to Bayesian Filtering and Smoothing]]
* [[Tutorials#tutorial25| T25 Sensor Fusion for Intelligent Vehicles]]
* [[Tutorials#tutorial26| T26 Multisensor Data Fusion in Wireless Sensor and Actuator Networks]]

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<div id="timetable"></div>
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #d6bdde; text-align:left; color:#000; padding:0.2em 0.4em;">Time Table for the Tutorials Day on Tuesday, July 5, 2016</h2>
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{| class="wikitable" style="text-align:center;background-color:#e7deef;"
{| {{table}}
! style="width:8em;text-align:center;background-color:#e7deef;"|'''Start & end times'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 1'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 2'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 3'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 4'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 5'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 6'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 7'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 8'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 9'''
|-
|style="text-align:center;background-color:#e7deef;" | '''Morning'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial1| T1]]'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial2| T2]]'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial3| T3]]'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial4| T4]]'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial15| T15]]'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial14| T14]]'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial7| T7]]'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial8| T8]]'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial9| T9]]'''
|-
|style="text-align:center;background-color:#e7deef;" | '''08:30 - 11:30'''
|style="text-align:center;background-color:#f7eff7;" | Bayesian Multiple Target Tracking<br />
''Stone, Streit''
|style="text-align:center;background-color:#f7eff7;" | Bayesian Networks and Trust Fusion with Subjective Logic<br />
''Jøsang''
|style="text-align:center;background-color:#f7eff7;" | Multisensor-Multitarget Tracker/Fusion Engine …<br />
''Kiruba''
|style="text-align:center;background-color:#f7eff7;" | … Track-to-Track Fusion and the Distributed Kalman Filter<br />
''Govaers''
|style="text-align:center;background-color:#f7eff7;" | Big Data Fusion and Analytics<br />
''Das''
|style="text-align:center;background-color:#f7eff7;" | Multistatic Exploration ... Modern Passive Radar …<br />
''Koch''
|style="text-align:center;background-color:#f7eff7;" | Multitarget Tracking and Multisensor Information Fusion<br />
''Bar-Shalom''
|style="text-align:center;background-color:#f7eff7;" | Overview of High-Level Information Fusion Theory …<br />
''Blasch''
|style="text-align:center;background-color:#f7eff7;" | Quantum Physics Methods For Nonlinear Filtering<br />
''Balaji, Daum''
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{| {{table}}
|style="width:7em;text-align:center;background-color:#e7deef;"| '''11:30-12:30'''
|style="width:15em;text-align:center;background-color:#f7eff7;"|
|style="width:15em;text-align:center;background-color:#f7eff7;"|
|style="width:15em;text-align:center;background-color:#f7eff7;"|
|style="width:15em;text-align:center;background-color:#f7eff7;"|
|style="width:15em;text-align:center;background-color:#f7eff7;"|
'''Lunch break'''<br />

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{| {{table}}
! style="width:8em;text-align:center;background-color:#f7eff7;"|
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 1'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 2'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 3'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 4'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 5'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 6'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 7'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 8'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 9'''
|-
|style="text-align:center;background-color:#e7deef;" | '''Mid Day'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial10| T10]]'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutoria11| T11]]'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial12| T12]]'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial13| T13]]'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial6| T6]]'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial5| T5]]'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial16| T16]]'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial17| T17]]'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial18| T18A]]'''
|-
|style="text-align:center;background-color:#e7deef;" | '''12:30-15:30'''
|style="text-align:center;background-color:#f7eff7;" | Basic concepts in multi-object estimation<br />
''Clark, Delande, Houssineau''
|style="text-align:center;background-color:#f7eff7;" | System-of-Systems … Issues for Information Fusion<br />
''Steinberg''
|style="text-align:center;background-color:#f7eff7;" | ... random-finite-set-based multi-target filters<br />
''Vo, Vo''
|style="text-align:center;background-color:#f7eff7;" | Tracking and Sensor Data Fusion ... Framework …<br />
''Koch''
|style="text-align:center;background-color:#f7eff7;" | Information Quality in Information Fusion …<br />
''Rogova''
|style="text-align:center;background-color:#f7eff7;" | ... Finite-Set Statistics for Information Fusion<br />
''Mahler''
|style="text-align:center;background-color:#f7eff7;" | Object tracking, sensor fusion ... self-driving vehicles …<br />
''Kiruba''
|style="text-align:center;background-color:#f7eff7;" | Emerging Quantum Technologies for Fusion<br />
''Balaji''
|style="text-align:center;background-color:#f7eff7;" | Maneuvering Target Tracking ... Filtering Methods<br />
''Li, Jilkov''
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|style="width:7em;text-align:center;background-color:#e7deef;"| '''15:30-16:00'''
|style="width:15em;text-align:center;background-color:#f7eff7;"|
|style="width:15em;text-align:center;background-color:#f7eff7;"|
|style="width:15em;text-align:center;background-color:#f7eff7;"|
|style="width:15em;text-align:center;background-color:#f7eff7;"|
|style="width:15em;text-align:center;background-color:#f7eff7;"|
'''Coffee/tea break'''<br />

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! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 1'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 2'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 3'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 4'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 5'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 6'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 7'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 8'''
! style="width:15em;text-align:center;background-color:#e7deef;"|'''Room 9'''
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|style="text-align:center;background-color:#e7deef;" | '''Afternoon'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial18| T18B]]'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutoria19| T19]]'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial20| T20]]'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial21| T21]]'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial22| T22]]'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial23| T23]]'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial24| T24]]'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial25| T25]]'''
|style="text-align:center;background-color:#f7eff7;" | '''[[Tutorials#tutorial26| T26]]'''
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|style="text-align:center;background-color:#e7deef;" | '''16:00-19:00'''
|style="text-align:center;background-color:#f7eff7;" | Maneuvering Target Tracking ... Filtering Methods<br />
''Li, Jilkov''
|style="text-align:center;background-color:#f7eff7;" | Integration of Information to Identify Objects in Big Data<br />
''Shieh''
|style="text-align:center;background-color:#f7eff7;" | Extended Object Tracking: Theory and Applications<br />
''Granström, Reuter, Baum''
|style="text-align:center;background-color:#f7eff7;" | Probabilistic situation assessment for abnormal …<br />
''Regazzoni, Marcenaro''
|style="text-align:center;background-color:#f7eff7;" | Multitarget tracking and sensor calibration in ... networks<br />
''Uney, Julier, Clark''
|style="text-align:center;background-color:#f7eff7;" | Information fusion in resource-limited camera networks<br />
''Cavallaro,SanMiguel''
|style="text-align:center;background-color:#f7eff7;" | Introduction to Bayesian Filtering and Smoothing<br />
''Särkkä''
|style="text-align:center;background-color:#f7eff7;" | Sensor Fusion for Intelligent Vehicles<br />
''Duraisamy, Yuan, Schwarz, Fritzsche''
|style="text-align:center;background-color:#f7eff7;" | Multisensor Data Fusion in Wireless ... Networks<br />
''Miceli de Farias''
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|style="width:7em;text-align:center;background-color:#e7deef;"| '''19:00-22:00'''
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'''Welcome Reception'''<br />

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{| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;"
<div id="tutorial1">

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{| id="mp-left" style="width:100%; vertical-align:top; background:#f9d6c9;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#f5baa3; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f36766; text-align:left; color:#000; padding:0.2em 0.4em;">T1 Bayesian Multiple Target Tracking</h2>
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'''Presenter:''' [mailto:stone@metsci.com Lawrence D. Stone] and Roy L. Streit<br />
'''Length:''' 3 hours<br />
'''Brief description:''' This tutorial is based on the book, Bayesian Multiple Target Tracking 2nd Ed. Its purpose is to present the basic results in multiple-target tracking from a Bayesian point of view. People who register will receive a complimentary copy of the book when they attend the tutorial.<br />
[[T1| More Details]]
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{| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;"
<div id="tutorial2"></div>

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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"

| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#ceecf2; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3babf; text-align:left; color:#000; padding:0.2em 0.4em;">T2 Bayesian Networks and Trust Fusion with Subjective Logic</h2>
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'''Presenter:''' [mailto:audun.josang@mn.uio.no Audun Jøsang]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' This tutorial gives attendees a first-hand insight into the theory and application of subjective logic by the author and researcher who proposed and started developing this framework in 1997. The tutorial gives an introduction to subjective logic, and how it applies to Bayesian network modelling and information fusion. ...<br />
[[T2| More Details]]
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{| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;"
<div id="tutorial3"></div>

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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#d6efd6; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #bdd6c6; text-align:left; color:#000; padding:0.2em 0.4em;">T3 Multisensor-Multitarget Tracker/Fusion Engine Development and Performance Evaluation for Realistic Scenarios</h2>
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'''Presenter:''' [mailto:kiruba@mcmaster.ca T. Kirubarajan]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' While numerous tracking and fusion algorithms are available in the literature, their implementation and application on real-world problems are still challenging. Since new algorithms continue to emerge, rapidly prototyping them, developing for production and evaluating them on real-world (or realistic) problems efficiently are also essential. In addition to reviewing state-of-the-art tracking algorithms, this tutorial will focus on a number of realistic multisensor-multitarget tracking problems, simulation of large-scale tracking scenarios, rapid prototyping, development of high performance real-time tracking/fusion software, and performance evaluation on realistic scenarios. ...<br />
[[T3| More Details]]
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{| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;"
<div id="tutorial4"></div>

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{| id="mp-left" style="width:100%; vertical-align:top; background:#ffffe8;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#fff7bd; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f2ea7e; text-align:left; color:#000; padding:0.2em 0.4em;">T4 An Introduction to Track-to-Track Fusion and the Distributed Kalman Filter</h2>
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'''Presenter:''' [mailto:felix.govaers@fkie.fraunhofer.de Felix Govaers]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' The increasing trend towards connected sensors (”internet of things” and ”ubiquitous computing”) derive a demand for powerful distributed estimation methodologies. In tracking applications, the ”Distributed Kalman Filter” (DKF) provides an optimal solution under certain conditions. The optimal solution in terms of the estimation accuracy is also achieved by a centralized fusion algorithm which receives either all associated measurements or so-called tracklets.... Two more recent methodologies are based on the ”accumulated state densities” (ASD) which augment the states from multiple time instants. In practical applications, tracklet fusion based on the equivalent measurement often achieves reliable results even if full communication is not available. The limitations and robustness of the tracklet fusion will be discussed. ...<br />
[[T4| More Details]]
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{| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;"
<div id="tutorial5"></div>

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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #d6bdde; text-align:left; color:#000; padding:0.2em 0.4em;">T5 An Introduction to Finite-Set Statistics for Information Fusion</h2>
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'''Presenter:''' [mailto:mahlerronald@comcast.net Ronald Mahler]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' Finite-set statistics is a theoretically unified mathematical machine for solving information fusion problems, based on random set theory. First systematically described in Statistical Multisource-Multitarget Information Fusion (Artech, 2007), it has attracted the interest of dozens of research groups in at least 19 nations, resulting in well over a thousand publications. Advances in Statistical Multisource-Multitarget Information Fusion (Artech, 2014) systematically described the most intriguing aspects of this research, including algorithms that outperform conventional approaches. Previous tutorials have focused on applications of random set information fusion. This is the first systematic tutorial treatment of finite-set statistics itself. ...<br />
[[T5| More Details]]
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<div id="tutorial6">

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{| id="mp-left" style="width:100%; vertical-align:top; background:#f9d6c9;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#f5baa3; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f36766; text-align:left; color:#000; padding:0.2em 0.4em;">T6 Information Quality in Information Fusion and Decision Making</h2>
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'''Presenter:''' [mailto:rogovagl@gmail.com Galina Rogova]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' ... The tutorial will discuss major challenges and some possible approaches addressing the problem of representing and incorporating information quality into fusion processes. In particular it will present an ontology of quality of information and identify potential methods of representing and assessing the values of quality attributes and their combination. It will also examine the relation between information quality and context, and suggest possible approaches to quality control compensating for insufficient information and model quality.<br />
[[T6| More Details]]
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<div id="tutorial7"></div>

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| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#ceecf2; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3babf; text-align:left; color:#000; padding:0.2em 0.4em;">T7 Multitarget Tracking and Multisensor Information Fusion</h2>
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'''Presenter:''' [mailto:ybs@engr.uconn.edu Yaakov Bar-Shalom]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' To provide to the participants the latest state-of-the art techniques to estimate the states ofmultiple targets with multisensor information fusion. Tools for algorithm selection, design and evaluation willbe presented. These form the basis of automated decision systems foradvanced surveillanceandtargeting.The various information processing configurations for fusion are described, including the recently solvedtrack-to-track fusion from heterogeneous sensors.<br />
[[T7| More Details]]
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{| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;"
<div id="tutorial8"></div>

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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#d6efd6; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #bdd6c6; text-align:left; color:#000; padding:0.2em 0.4em;">T8 Overview of High-Level Information Fusion Theory, Models, and Representations</h2>
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'''Presenter:''' [mailto:erik.blasch@gmail.com Erik Blasch]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' Over the past decade, the ISIF community has put together special sessions, panel discussions, and concept papers to capture the methodologies, directions, needs, and grand challenges of high-level information fusion (HLIF) in practical system designs. This tutorial brings together the contemporary concepts, models, and definitions to give the attendee a summary of the state-of-the-art in HLIF. Analogies from low-level information fusion (LLIF) of object tracking and identification are extended to the HLIF concepts of situation/impact assessment and process/user refinement. HLIF theories (operational, functional, formal, cognitive) are mapped to representations (semantics, ontologies, axiomatics, and agents) with contemporary issues of modeling, testbeds, evaluation, and human-machine interfaces. Discussions with examples of search and rescue, cyber analysis, and battlefield awareness are presented. ...<br />
[[T8| More Details]]
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{| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;"
<div id="tutorial9"></div>

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{| id="mp-left" style="width:100%; vertical-align:top; background:#ffffe8;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#fff7bd; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f2ea7e; text-align:left; color:#000; padding:0.2em 0.4em;">T9 Quantum Physics Methods for Nonlinear Filtering</h2>
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'''Presenter:''' [mailto:Bhashyam.Balaji@drdc-rddc.gc.ca Bhashyam Balaji] and [mailto:Frederick_E_Daum@raytheon.com Fred Daum]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' Relationships between nonlinear filtering and quantum physics has been studied in the past. In this tutorial, more modern connections between the two fields are drawn, particularly based on methods drawn from Feynman path integrals, quantum field theory and renormalization group.<br />
[[T9| More Details]]
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{| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;"
<div id="tutorial10"></div>

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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #d6bdde; text-align:left; color:#000; padding:0.2em 0.4em;">T10 Basic Concepts in Multiobject Estimation</h2>
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'''Presenter:''' [mailto:D.E.Clark@hw.ac.uk Daniel Clark], Emmanuel D. Delande, and Jérémie Houssineau<br />
'''Length:''' 3 hours<br />
'''Brief description:''' ... This tutorial will highlight some basic mathematical concepts in multiobject estimation to enable researchers to better understand and contribute to innovations in this field. The goal of the presenters is to inspire participants to develop a broader mathematical perspective and explore the literature in spatial statistics and point processes to aid their research in sensor fusion. The presenters will highlight where new concepts to multiobject estimation in sensor fusion, such as regional variance for estimating population uncertainty, can be facilitated when considering a measuretheoretic point process perspective.<br />
[[T10| More Details]]
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<div id="tutorial11">

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{| id="mp-left" style="width:100%; vertical-align:top; background:#f9d6c9;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#f5baa3; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f36766; text-align:left; color:#000; padding:0.2em 0.4em;">T11 System-of-Systems Concepts, Opportunities and Issues for Information Fusion</h2>
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'''Presenter:''' [mailto:alaneilsteinberg@gmail.com Alan Steinberg]<br />
'''Length:''' 3 hours <br />
'''Brief description:''' Current concepts and methods in System-of-Systems Engineering (SoSE) will be presented, together with the role of information fusion. ... Methods for maximizing the effectiveness of cooperative sensing and cooperative engagement tactics will be discussed. ... Advanced multi-sensor, highly integrated weapons platforms provide enormous new capabilities. ... Data integrity and consistency are critical in integrating and using systems-of-systems. Attendees will learn current techniques for aligning data in space and time and in confidence. ... There will be discussion of SoS Engineering methodology for developing SoS architectural and management solutions to meet requirements of technical performance, cost, flexibility and extensibility. Developmental and operational testing and evaluation of systems-of-systems involves special challenges, not the least of which are multiple interacting control-loops in such systems.<br />
[[T11| More Details]]
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{| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;"
<div id="tutorial12"></div>

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| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#ceecf2; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3babf; text-align:left; color:#000; padding:0.2em 0.4em;">T12 Implementations of Random-Finite-Set-Based Multi-Target Filters</h2>
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'''Presenter:''' [mailto:ba-ngu.vo@curtin.edu.au Ba-Ngu Vo] and Ba-Tuong Vo<br />
'''Length:''' 3 hours<br />
'''Brief description:''' The Finite Set Statistics framework for multi-sensor multi-target tracking has attached considerable interest in recent years. It provides a unified perspective of multi-target tracking in a very intuitive manner by drawing direct parallels with the simpler problem of single-target tracking. This framework has lead to the development of multi-target filters such as the Probability Hypothesis Density (PHD), Cardinalized PHD (CPHD), Multi-Bernoulli filters and recently, the Generalized Labeled Multi-Bernoulli filter. In this tutorial, we show how these filters are implemented and illustrate via Matlab how these filters work. ...<br />
[[T12| More Details]]
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{| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;"
<div id="tutorial13"></div>

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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#d6efd6; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #bdd6c6; text-align:left; color:#000; padding:0.2em 0.4em;">T13 Tracking and Sensor Data Fusion – Methodological Framework and Selected Applications</h2>
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'''Presenter:''' [mailto:wolfgang.koch@fkie.fraunhofer.de Wolfgang Koch]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' The tutorial covers the material of the recently published book of the presenter with the same title (Springer 2014, Mathematical Engineering Series, ISBN 978-3-642-39270-2) and thus provides an guided introduction to deeper reading. Starting point is the well known JDL model of sensor data and information fusion that provides general orientation within the world of fusion methodologies and its various applications, covering a dynamically evolving field of ever increasing relevance. Using the JDL model as a guiding principle, the tutorial introduces into advanced fusion technologies based on practical examples taken from real world applications.<br />
[[T13| More Details]]
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{| id="mp-upper" style="width: 80%; margin:4px 0 0 0; background:none; border-spacing: 0px;"
<div id="tutorial14"></div>

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{| id="mp-left" style="width:100%; vertical-align:top; background:#ffffe8;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#fff7bd; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f2ea7e; text-align:left; color:#000; padding:0.2em 0.4em;">T14 Multistatic Exploration – Introduction to Modern Passive Radar and Multistatic Tracking & Data Fusion</h2>
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'''Presenter:''' [mailto:wolfgang.koch@fkie.fraunhofer.de Wolfgang Koch]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' Advanced distributed signal and data fusion for passive radar systems, where DVB TV or GSM mobile phone base stations are used as sources for illuminating targets, for example, is a topic of increasing interest. Even in remote regions of the world, transmitters of electromagnetic radiation become a potential radar transmitter stations enabling covert surveillance for air, sea, and ground scenarios. Analogous considerations are valid for sub-sea surveillance. Illustrated by examples and experimental results, principles of passive radar as well as advanced multistatic tracking and de-ghosting techniques will be discussed.<br />
[[T14| More Details]]
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| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #d6bdde; text-align:left; color:#000; padding:0.2em 0.4em;">T15 Big Data Fusion and Analytics</h2>
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'''Presenter:''' [mailto:sdas@machineanalytics.com Subrata Das]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' Big data has tremendous potential to transform businesses but poses significant challenge in searching, processing, and extracting actionable intelligence. In this tutorial, I will present some techniques for fusion and analytics to process big centralized warehouse data, inherently distributed data, and data residing on the cloud. The fusion and analytics techniques to be discussed will handle both structured transactional and sensor data as well as unstructured textual data such as human intelligence, emails, blogs, surveys, etc. As a background, this tutorial is intended to provide an account of both the cutting-edge and the most commonly used approaches to high-level data fusion and predictive and text analytics. The demos to be presented are in the areas of distributed search and situation assessment, information extraction and classification, and sentiment analyses. ...<br />
[[T15| More Details]]
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<div id="tutorial16">

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{| id="mp-left" style="width:100%; vertical-align:top; background:#f9d6c9;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#f5baa3; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f36766; text-align:left; color:#000; padding:0.2em 0.4em;">T16 Object Tracking, Sensor Fusion and Situational Awareness for Assisted- and Self-Driving Vehicles: Problems, Solutions and Directions</h2>
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'''Presenter:''' [mailto:kiruba@mcmaster.ca T. Kirubarajan]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' ... In this tutorial, we aim to discuss a number of problems related to assisted- and self-driving vehicles, potential solutions and directions for research & development. The issues discussed in this tutorial will span multitarget tracking, multisensor fusion and situational awareness within the context of smart cars. We will also present some of the algorithms that are available in the open literature as well as those we have developed recently. In addition, we will also discuss related computational issues and sensor technologies. Finally, we will present some results on real data.<br />
[[T16| More Details]]
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<div id="tutorial17"></div>

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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"

| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#ceecf2; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3babf; text-align:left; color:#000; padding:0.2em 0.4em;">T17 Emerging Quantum Technologies for Fusion</h2>
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'''Presenter:''' [mailto:Bhashyam.Balaji@drdc-rddc.gc.ca Bhashyam Balaji]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' ... Although the fundamentals of quantum physics have been well-known since the 1920s, in the last few decades several novel consequences of the laws of quantum physics (particularly, in the areas of atomic, molecular and optical physics and quantum computer science and information theory) have been discovered. ... In particular, in the areas of sensing, quantum physics sets the bounds on the sensitivity of sensing... that is orders of magnitude below the sensitivity of current sensors. In the area of computing, it has been observed that a quantum computer allows some computations to be carried out that are unfeasible using current or future classical computing technology. In the area of communication, quantum physics enables provable secure communication and at much higher data rates than those allowed by classical Shannon limit. Many of these advances could have major near-term and long-term consequences in the areas of sensing, secure communication, big data analysis, and machine learning, and hence sensor and information fusion.<br />
[[T17| More Details]]
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<div id="tutorial18"></div>

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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#d6efd6; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #bdd6c6; text-align:left; color:#000; padding:0.2em 0.4em;">T18 Maneuvering Target Tracking: Overview and Nonlinear Filtering Methods</h2>
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'''Presenter:''' [mailto:XLi@uno.edu X. Rong Li] and [mailto:vjilkov@uno.edu Vesselin P. Jilkov]<br />
'''Length:''' 3+3 hours<br />
'''Brief description:''' The principal challenges for tracking a maneuverable target are nonlinearity in both target motion and measurement models as well as the uncertainty in the pattern of target motion. This tutorial presents theoretical and algorithmic means available to meet these challenges. The overview part elucidates a well organized panorama of maneuvering target tracking. The other part presents an in-depth coverage of recent advances in nonlinear filtering for maneuvering target tracking, including some of the instructors’ results and insights as well as better known methods. The tutorial highlights the underlying ideas and pros and cons of approaches and techniques as well as inter-relationships among them. It is an outgrowth of the instructors’ ongoing comprehensive survey and several short courses of the same subject as well as a graduate course on target tracking taught at the Electrical Engineering Department of the University of New Orleans.<br />
[[T18| More Details]]
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<div id="tutorial19"></div>

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{| id="mp-left" style="width:100%; vertical-align:top; background:#ffffe8;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#fff7bd; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f2ea7e; text-align:left; color:#000; padding:0.2em 0.4em;">T19 Integration of Information to Identify Objects in Big Data</h2>
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'''Presenter:''' [mailto:gshieh@webmail.stat.sinica.edu.tw Grace S. Shieh]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' Big data has tremendous potential to transform businesses and research but raises significant challenges in pre-processing and extracting useful information and information integration to identify objects of interest. In this tutorial, I will present some statistical methods/machine learning for fusion and analysis of big data in cancer research, e.g., DNA sequencing data, gene expression data (RNA-seq) from The Cancer Genome Atlas (TCGA), protein expression and clinical features of cancer patients. This tutorial aims to cover both useful statistical/data mining methods and the cutting-edge directions. ...<br />
[[T19| More Details]]
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #d6bdde; text-align:left; color:#000; padding:0.2em 0.4em;">T20 Extended Object Tracking: Theory and Applications</h2>
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'''Presenter:''' [mailto:karl.granstrom@chalmers.se Karl Granström], Stephan Reuter, and [mailto:marcus.baum@cs.uni-goettinge.de Marcus Baum]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' Autonomous driver safety functions are standard in many modern cars, and semi-automated systems (e.g., traffic jam assist) are becoming more and more common. Construction of a driverless vehicle requires solutions to many different problems, among them multiple object tracking. This tutorial will introduce the audience to extended object tracking, i.e., object tracking using modern high resolution sensors that give multiple detections per object. State of the art theory will be introduced, and relevant real world applications will be shown where different object types—e.g., pedestrians, bicyclists, cars—are tracked using different sensors such as lidar, radar, and camera.<br />
[[T20| More Details]]
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{| id="mp-left" style="width:100%; vertical-align:top; background:#f9d6c9;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#f5baa3; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f36766; text-align:left; color:#000; padding:0.2em 0.4em;">T21 Probabilistic Situation Assessment for Abnormal Interaction Detection</h2>
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'''Presenter:''' [mailto:carlo.regazzoni@unige.it Carlo Regazzoni] and [mailto:lucio.marcenaro@unige.it Lucio Marcenaro]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' The tutorial aims at providing an overview of new insights in extending Dynamic Bayesian Networks techniques for representing, modeling and automatically interpreting and managing complex interaction situations occurring in cognitive environments starting from observations provided by multidimensional signals collected through a distributed network of embedded systems. A uniform representation is discussed that can also be used to support decisions concerning interactions between operators and the status of the observed environment. Solutions, which are based on an extension of traditional Bayesian filters for object assessment, are the basis background of discussion from which techniques in this tutorial. ...<br />
[[T21| More Details]]
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"

| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#ceecf2; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3babf; text-align:left; color:#000; padding:0.2em 0.4em;">T22 Multitarget Tracking and Sensor Calibration in Centralized and Distributed Networks</h2>
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'''Presenter:''' Murat Uney, Simon Julier, and [mailto:D.E.Clark@hw.ac.uk Daniel Clark]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' … This tutorial will present methods for fusion and registration in networks of sensors. In the first part, the focus will be on integrating information output by local filtering at the sensor nodes. Both optimal and suboptimal algorithms will be presented and discussed. The second part will cover registration/calibration of sensors. First, a centralised setting will be considered in which the sensor measurements are available at a centre. It will be shown how the registration process can exploit the Probability Hypothesis Density (PHD) filtering principles for handling the uncertainties in the multitarget model. The second topic will be a distributed setting in which several sensor nodes exchange filtered distributions as opposed to measurements. A recent solution will be introduced which feature local processing at the sensor nodes and message passing operations for selfcalibration.<br />
[[T22| More Details]]
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#d6efd6; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #bdd6c6; text-align:left; color:#000; padding:0.2em 0.4em;">T23 Information Fusion in Resource-Limited Camera Networks</h2>
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'''Presenter:''' [mailto:a.cavallaro@qmul.ac.uk Andrea Cavallaro] and [mailto:juancarlos.sanmiguel@uam.es Juan C. SanMiguel]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' … This tutorial will introduce key features of modern visual sensor networks while exploring the issues commonly found in such networks, which have recently become central in several applications. For smart-camera networks to enable these emerging applications they need to adapt to unforeseen conditions and varying tasks under constrained resources. The tutorial will offer theoretical explanations followed by examples using the WiseMNet++ simulator.<br />
[[T23| More Details]]
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{| id="mp-left" style="width:100%; vertical-align:top; background:#ffffe8;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#fff7bd; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f2ea7e; text-align:left; color:#000; padding:0.2em 0.4em;">T24 Introduction to Bayesian Filtering and Smoothing</h2>
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'''Presenter:''' [mailto:simo.sarkka@aalto.fi Simo Särkkä]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' ... The tutorial introduces the current state-of-the-art of non-linear (single-target) optimal filtering and smoothing methods in a unified Bayesian framework. The attendees learn what non-linear Kalman filters and particle filters are, how they are related, and their relative advantages and disadvantages. They also discover how Bayesian parameter estimation methods can be combined with the filtering and smoothing algorithms. ... Example applications from navigation, remote surveillance, and time series analysis.<br />
[[T24| More Details]]
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{| id="mp-left" style="width:100%; vertical-align:top; background:#e7f7e76;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:4px; background:#e7deef; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #d6bdde; text-align:left; color:#000; padding:0.2em 0.4em;">T25 Sensor Fusion for Intelligent Vehicles</h2>
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'''Presenter:''' [mailto:bharanid-har.duraisamy@daimler.com Bharanidhar Duraisamy], [mailto:ting.yuan@daimler.com Ting Yuan], [mailto:tilo.schwarz@daimler.com Tilo Schwarz], and [mailto:martin.fritzsche@daimler.com Martin Fritzsche]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' This tutorial is focussed towards the stringent requirements, foundations, development and testing of sensor fusion algorithms meant for advanced driver assistance functions and driverless applications in automotive vehicle systems. ... The interesting part of the tutorial is covered on the different challenging and important practical aspects such as fusion with incomplete information, data association, etc. related to fusion and target tracking in automotive setting. Fusion and management of the different extended target representations of heterogeneous nature obtained from sensors with different resolution is presented with examples. More than one art of intelligent vehicular sensor fusion framework dealing with tracked objects i.e. track level fusion and raw sensor measurements i.e. measurement level fusion, with results obtained using several real world data sets that contains various static and dynamic targets would be presented in this tutorial.<br />
[[T25| More Details]]
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{| id="mp-left" style="width:100%; vertical-align:top; background:#f9d6c9;"
| style="padding:2px;" | <h2 id="mp-tfa-h2" style="margin:3px; background:#f5baa3; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #f36766; text-align:left; color:#000; padding:0.2em 0.4em;">T26 Multisensor Data Fusion in Wireless Sensor and Actuator Networks</h2>
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'''Presenter:''' [mailto:cmicelifarias@gmail.com Claudio Miceli de Farias]<br />
'''Length:''' 3 hours<br />
'''Brief description:''' This tutorial focuses on presenting Multisensor Data Fusion Techniques for Wireless Sensor and Actuator networks. Advances in microelectromechanical systems technologies and wireless communications have enabled the construction of devices, called sensors, endowed with processing and communication capabilities, used to monitor physical quantities in an environment. ... Recent years have witnessed the emergence of the Shared/ Virtual Sensor and Actuator Networks, which instead of assuming an application-specific design, allow the sensing and communication infrastructure to be shared among multiple applications. ... However, wireless sensors and actuators commonly rely on batteries as their energy sources, whose replacement is undesirable or unfeasible. Therefore, in order to reduce the amount of data to be transmitted in the wireless channel, thus saving energy, Multisensor Data Fusion Methods (MDF) can be employed.<br />
[[T26| More Details]]
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__NOTOC____NOEDITSECTION__

Author guidelines

2016-02-29T13:19:06Z

Hanebeck:

__NOTOC__


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* A1 - Authors must submit their own original works only.

* A2 - Authors must not omit the main references done by others and related to their works.

* A3 - Authors must follow typesetting guidelines (templates) of the ISIF JAIF Journal or of the ISIF Fusion conference.

* A4 - Authors must agree with ISIF copyright agreement, once the paper is accepted for publication.

* A5 - Authors must employ professional language and they must avoid excessive verbosity that would dilute the technical clarity.

For the FUSION conferences, following guidelines also apply
* F1 Papers must be presented at the conference.
* F2 Critical technical comments of technical reviewers and the technical program committee must be adequately reflected in the final manuscript.


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Submitted papers published on the Fusion 2016 Conference Proceedings must meet established IEEE and ISIF standards and requirements. These apply to post-conference distribution of the Conference Proceedings as well, including submission to IEEE Xplore.
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All papers must be formatted according to the IEEE Xplore template (letter size paper). Templates and other supporting files for various types of computers and operational systems can be downloaded using the following links:
* [http://www.fusion2016.org/download/fusion2016_template.zip Fusion 2016 LaTeX template]
* [http://www.fusion2016.org/download/IEEEtran_HOWTO.pdf Usage instructions for LaTeX template]
* [http://www.fusion2016.org/download/fusion2016_template.doc Fusion 2016 Microsoft Word template]
*[http://www.ieee.org/documents/ieeecopyrightform.pdf Copyright Form]

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The initial submission of each paper for the review process consists of a unique file, in PDF format. The paper title and authors must match the information entered in the EDAS system. Papers should be strictly no fewer than 4 pages, and preferably no more than 8 pages in length. There will be a charge of € 100 for each additional page beyond 8 pages. Shorter submissions might be automatically rejected by the system, otherwise they will be rejected during the review process.

Note that the above length (4-8 pages) is based on the submission template adopted by the Fusion 2016 conference, which is available in different formats via the links above. Changes to the template formatting standards, such as modifying the font size (9 points for the abstract, 10 points for the text, etc.) will disqualify the submission.

Submission of final versions of accepted papers (i.e., camera-ready submissions) must include a copyright form. To prepare their copyright forms, authors should download the copyright form and perform either of the two alternatives for having it signed:

# Print, manually sign, and scan the signed form.
# Digitally sign the form (e.g. using Adobe Acrobat™)

After papers are accepted, a link will be made available to authors in EDAS by which completed copyright forms can be uploaded. There is no need to include the copyright form with the initial submission.

The conference proceedings will have its own formatting with respect to numbering and identification. Therefore, papers should not include page numbers or conference name.
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