1st IEEE Workshop on Performance Evaluation of Tracking and Surveillance (PETS2000)

Motion Detection and Tracking using Belief Indicators for Video Surveillance Applications

Cina Motamed

Laboratoire LASL, Universite du Lottoral Cote d'Opale, Calais, France.

A video-surveillance system for human and car activity monitoring is presented and evaluated over a car park test sequence. Our strategy is to illustrate how history of events can help decisions in the video-surveillance algorithms. In the algorithms this history reflecting the persistance of a fact is resumed as a indicator updated at each sequence. = =20 The first stage of the video surveillance concerns the motion detection process in order to highlight interesting object. An updating of the back ground reference is proposed in order to control changes in illumination and the object integration. The control of this object integration at each pixel is based on the stabibility indicator of the current reference . The tracking step is a 2D approach of region tracking working over a variety of applications. An associate belief indicator resuming history of tracking quality for each object permits to manage a majorities of ambiguities. These algorithms are tested with pets-2000 data-set, and discussed particularly when ambiguities appear.


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[5] P.VANNOORENBERGHE, C. MOTAMED, J.-M. BLOSSEVILLE & J.-G. POSTAIRE. 'Automatic Pedestrian Recognition using Real Time Motion Analysis' Conference : ICIAP 97 Image Analysis and Processing, Florence, Italia, Septembre 1997, pp 493-500.

Last Modified 3 March 2000 18:46