Title :
Multi-object tracking using the particle filter algorithm on the top-view plan
Author :
Martnez, Santiago Venegas ; Knebel, Jean-Francois ; Thiran, Jean-Philippe
Author_Institution :
Signal Process. Inst., Swiss Fed. Inst. of Technol. (EPFL), Lausanne, Switzerland
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.
Keywords :
computational complexity; image reconstruction; image sequences; object tracking; particle filtering (numerical methods); pedestrians; video signal processing; ambiguity conditions; computational complexity reduction; multiobject tracking; particle filter technique; pedestrian tracking; robust tracking framework; top-view reconstruction; video sequences; Abstracts; Adaptation models; Filtering algorithms; Information filters; Monitoring; Real-time systems;
Conference_Titel :
Signal Processing Conference, 2004 12th European
Conference_Location :
Vienna
Print_ISBN :
978-320-0001-65-7