Multi-Object Tracking Based on Particle Filter and Data Association in Color Image Sequences

Authors:
Ayoub Al-Hamadi;Saira Saleem Pathan;Bernd Michaelis
Affiliations:
Institute for Electronics, Signal Processing and Communications (IESK), Otto-von-Guericke-University Magdeburg, Germany;Institute for Electronics, Signal Processing and Communications (IESK), Otto-von-Guericke-University Magdeburg, Germany;Institute for Electronics, Signal Processing and Communications (IESK), Otto-von-Guericke-University Magdeburg, Germany
Venue:
ICCVG 2008 Proceedings of the International Conference on Computer Vision and Graphics: Revised Papers
Year:
2008

Citing 3
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Abstract

Robust tracking of multi-objects is still challenging in real scenarios such as crowed scenes. In this paper a novel method in color image sequences is proposed for tracking multiple objects in non-cooperative situations. A system of independent particle filters with an adaptive motion model is used which tracks the moving objects under complex situations. Besides, in order to handle the conflicted situations, an integrated data association technique is exploited which adjusts the particle filters accordingly. Results have shown the good performance of the proposed method on various complex-situation image sequences.