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.
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© 2006 Springer-Verlag Berlin Heidelberg
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Jin, T., Park, C., Park, S. (2006). Multi-agent Motion Tracking Using the Particle Filter in ISpace with DINDs. In: Yang, Q., Webb, G. (eds) PRICAI 2006: Trends in Artificial Intelligence. PRICAI 2006. Lecture Notes in Computer Science(), vol 4099. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-36668-3_134
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DOI: https://doi.org/10.1007/978-3-540-36668-3_134
Publisher Name: Springer, Berlin, Heidelberg
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