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Long Term Multi-Target Tracking based on Detection and Data Association

Ai Min Li 1 and Pil Seong Park 2
1. Shandong Polytechnic University, Jinan, China
2. University of Suwon, Suwon, Korea
Abstract—Multi-target tracking is widely studied, but it is still an attractive but difficult research area because of existence of occlusion and interaction between target images. We propose a novel detection-based multi-target tracking method using data association. The main contribution of our method is providing a strategy to quickly correct the wrong tracker aroused by occlusion. We use somewhat unreliable detection confidence to assist a particle filter tracker. The resulting algorithm is tested using movies having much occlusion. The result shows good performance, fast enough to run real time for a relatively long period of time.

Index Terms—multi-target tracking, Particle filter, Hungarian algorithm, data association

Cite: Ai Min Li and Pil Seong Park, "Long Term Multi-Target Tracking based on Detection and Data Association," International Journal of Electronics and Electrical Engineering, Vol. 1, No. 3, pp. 124-129, September 2013. doi: 10.12720/ijeee.1.3.124-129
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