Object tracking and automated video annotation

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Object tracking and automated video annotation. Anca Croitor Sava – Timisoara, ROMANIA Ágnes Bartha – Budapest, HUNGARY Camelia Popa – Cluj-Napoca, ROMANIA Sándor Fazekas – Budapest, HUNGARY Tamás Ungi – Szeged, HUNGARY. Contents. Who? What? How? Why?. Who?. The orange ball - PowerPoint PPT Presentation

Transcript of Object tracking and automated video annotation

  • Object tracking and automated video annotation Anca Croitor Sava Timisoara, ROMANIA gnes Bartha Budapest, HUNGARY Camelia Popa Cluj-Napoca, ROMANIA Sndor Fazekas Budapest, HUNGARY Tams Ungi Szeged, HUNGARY

  • Who?

    What?

    How?

    Why?

    Contents

  • Who?The orange ballPlayersA transferred from Juventus Torino for 5 meal ticketsB goal getter from Ajax AmsterdamC gained for 1mil $ and 10 meal ticketsDevelopment Team Agnes Head of Female Research Department Cami Public Relations Key AdvisorAnca Chief Web and Presentation DesignerTamas Chief Technology OfficerSandor Lead System Designer

  • 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

  • How?Video SequencePREPROCESINGHOUGH TRANSFORMCOLOR TESTBALL TRACKINGTRAJECTORY EVALUATIONKEY EVENTS EXTRACTIONVIDEO ANNOTATIONGAME MODEL

  • Ball trackingBall 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 matchingMeasure of similarity between image and template Normalized cross correlation - Dmitrij Csetverikov

    Color test to eliminate false detection use of more reference colors

  • Template matchingWhat to do if we find the ball, but on the next frame we loose it?Ball templateOur solution: - create a ball template - search for similarities on the next frame

  • Tracking by color quickest and easiest method

    its simplicity can cause the tracking to fail

  • Trajectory evaluation Evolution of ball position in timePixel coordinates of the ball during the game

  • Use of velocity for extracting the movement eventsAnnotating the ball:-in standby-in game process

  • Base level key events extractionBall is thrown from one player to the otherThe players carry the ballPlayers change place (according to the games rules)

  • High level key events extractionStatistics of standing as cat (macska)Game 1Game 2

  • Animation based on extracted informationANALYSIS PROGRAMkey eventsVisualization programText file 0 18 2 35 0 5670 1 800 for left1 for center2 for right

  • Animation based on extracted information

  • Future possibilitiesExtension - Physically correct motion modelTracking accuracy for automatic annotation of tennis matches

    Football game supervision

  • Thank you!!!