Abstract:
In this paper we address the problem of multi-object tracking in video sequences, with application to pedestrian tracking in a crowd. In this context, particle filters pr...Show MoreMetadata
Abstract:
In this paper we address the problem of multi-object tracking in video sequences, with application to pedestrian tracking in a crowd. In this context, particle filters provide a robust tracking framework under ambiguity conditions. The particle filter technique is used in this work, but in order to reduce its computational complexity and increase its robustness, we propose to track the moving objects by generating hypotheses not in the image plan but on the top-view reconstruction of the scene. Comparative results on real video sequences show the advantage of our method for multi-object tracking.
Published in: 2004 12th European Signal Processing Conference
Date of Conference: 06-10 September 2004
Date Added to IEEE Xplore: 06 April 2015
Print ISBN:978-320-0001-65-7
Conference Location: Vienna, Austria