Occlusion detection and recovery in video object tracking based on adaptive particle filters

Authors:
Zhuohua Duan;Zixing Cai;Jinxia Yu
Affiliations:
School of Computer Science, Shaoguan University, Shaoguan, China;School of Information Science and Engineering, Central South University, Changsha, China;Department of Computer Science & Technology, Henan Polytechnic University, Jiaozuo, China
Venue:
CCDC'09 Proceedings of the 21st annual international conference on Chinese Control and Decision Conference
Year:
2009

Citing 2
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Abstract

Occlusion detection and recovery is a challenging task in robust real-time tracking of non-rigid objects. Particle filtering has proven very successful for non-linear and non-Gaussian estimation problems. The paper presents a method for occlusion detection and recovery for object tracking with adaptive particle filter. Firstly, object occlusion is detected with normalization factor. Secondly, adaptive transition function is employed to recovery from occlusion. Lastly, particle number is changed according to occlusion state. Experimental results show the presented method can detect occlusion and recover from it quickly.