SSIP 2007 1 Object tracking and automated video annotation Anca Croitor Sava – Timisoara, ROMANIA...

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SSIP 2007 SSIP 2007 SSIP 2007 SSIP 2007 1 Object tracking and Object tracking and automated video automated video annotation annotation Anca Croitor Sava Anca Croitor Sava – Timisoara, – Timisoara, ROMANIA ROMANIA Ágnes Ágnes Bartha Bartha – Budapest, – Budapest, HUNGARY HUNGARY Camelia Popa Camelia Popa – Cluj-Napoca, – Cluj-Napoca, ROMANIA ROMANIA Sándor Fazekas Sándor Fazekas – Budapest, – Budapest, HUNGARY HUNGARY Tamás Ungi Tamás Ungi – Szeged, HUNGARY – Szeged, HUNGARY

Transcript of SSIP 2007 1 Object tracking and automated video annotation Anca Croitor Sava – Timisoara, ROMANIA...

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Object tracking and Object tracking and automated video annotationautomated video annotation

Anca Croitor SavaAnca Croitor Sava – Timisoara, ROMANIA – Timisoara, ROMANIA ÁgnesÁgnes BarthaBartha – Budapest, HUNGARY – Budapest, HUNGARY Camelia PopaCamelia Popa – Cluj-Napoca, ROMANIA – Cluj-Napoca, ROMANIA Sándor FazekasSándor Fazekas – Budapest, HUNGARY – Budapest, HUNGARY Tamás UngiTamás Ungi – Szeged, HUNGARY – Szeged, HUNGARY

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Who?Who?

What?What?

How?How?

Why?Why?

ContentsContents

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Who?Who?

The orange ballThe orange ball PlayersPlayers

A – transferred from Juventus Torino for 5 meal ticketsA – transferred from Juventus Torino for 5 meal tickets B – goal getter from Ajax AmsterdamB – goal getter from Ajax Amsterdam C – gained for 1mil $ and 10 meal ticketsC – gained for 1mil $ and 10 meal tickets

Development Team Development Team Agnes – Head of Female Research Department Agnes – Head of Female Research Department Cami – Public Relations Key AdvisorCami – Public Relations Key Advisor Anca – Chief Web and Presentation DesignerAnca – Chief Web and Presentation Designer Tamas – Chief Technology OfficerTamas – Chief Technology Officer Sandor – Lead System DesignerSandor – Lead System Designer

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What?What?

Input: video sequence of for example of part of a ball game match

Aim: to detect elements and key events

Output: - ball detection - video annotation - a computed game model - statistics of match

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How?How?

Video Sequence

PREPROCESING

HOUGH TRANSFORM

COLOR TEST

BALL TRACKING

TRAJECTORY EVALUATION

KEY EVENTS EXTRACTION

VIDEO ANNOTATION

GAME MODEL

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Ball trackingBall tracking Ball detection: Hough transformation for circlesBall detection: Hough transformation for circles - - Joakim Lindblad

P.V.C. Hough, Machine Analysis of Bubble Chamber Pictures, International Conference on High Energy Accelerators and Instrumentation, CERN, 1959.

Tracking: Template matchingTracking: Template matching Measure of similarity between image and template Measure of similarity between image and template Normalized cross correlation - Normalized cross correlation - Dmitrij Csetverikov

Color test to eliminate false detection – use of more Color test to eliminate false detection – use of more reference colors reference colors

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Template matchingTemplate matching

What to do if we find the ball, but on the next frame we loose it?

Ball template

Our solution:

- create a ball template

- search for similarities on the next frame

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Tracking by colorTracking by color• quickest and easiest method

• its simplicity can cause the tracking to fail

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Trajectory evaluation Trajectory evaluation

Evolution of ball position in timeEvolution of ball position in time Pixel coordinates of the ball during the gamePixel coordinates of the ball during the game

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Use of velocity for extracting the Use of velocity for extracting the movement eventsmovement events

Annotating the ball:Annotating the ball:-in standby-in standby-in game process-in game process

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Base level key events extractionBase level key events extraction

Ball is thrown from one player to the otherBall is thrown from one player to the other The players carry the ballThe players carry the ball Players change place (according to the Players change place (according to the

game’s rules)game’s rules)

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High level key events extractionHigh level key events extraction

Statistics of standing as cat (macska)Statistics of standing as cat (macska)

AA BB CC

11 22 22

00 22 11

Game 1

Game 2

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Animation based on extracted Animation based on extracted informationinformation

ANALYSIS PROGRAM

key events

Visualization program

Text file

12 0 1827 2 3540 0 5670 1 80

0 for left1 for center2 for right

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Animation based on extracted Animation based on extracted informationinformation

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Future possibilitiesFuture possibilities

Extension - Physically correct motion modelExtension - Physically correct motion model Tracking accuracy for automatic annotation of

tennis matches

Football game supervision

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Thank you!!!Thank you!!!