Multi-agent motion tracking using the particle filter in ISpace with DINDs

Authors:
TaeSeok Jin;ChangHoon Park;SooHong Park
Affiliations:
Dept. of Mechatronics Engineering, DongSeo University, Sasang-ku, Busan, Korea;Dept. of Game Engineering, Hoseo University, Asan, Chungnam, Korea;Dept. of Mechatronics Engineering, DongSeo University, Sasang-ku, Busan, Korea
Venue:
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Year:
2006

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Object Tracking with an Adaptive Color-Based Particle Filter

Proceedings of the 24th DAGM Symposium on Pattern Recognition

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Abstract

We present a method for representing, tracking and human following by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd. And the article presents the integration of color distributions into particle filtering. Particle filters provide a robust tracking framework under ambiguity conditions. 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. Simulations are carried out to evaluate the proposed performance. Also, the method is applied to the intelligent environment and its performance is verified by the experiments.