Occlusion Detection and Recovery in Video Object Tracking Based on Adaptive Particle Filters

摘要：

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.

关键词： Object tracking Particle Filter Occlusion detection Occlusion Recovery Adaptive

作者: Zhuohua Duan Zixing Cai Jinxia Yu

作者单位: School of Computer Science, Shaoguan University, Shaoguan 512005, China School of Information Science and Engineering, Central South University, Changsha 410083, China Department of Computer Science & Technology, Henan Polytechnic University, Jiaozuo454003, China

会议类型: 国际会议

会议名称: 2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)

会议地点: 广西桂林

会议语种:英文

页码: 466-469

在线出版日期: 2009-06-17（万方平台首次上网日期，不代表论文的发表时间）