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

被引：0

作者：

Duan, Zhuohua ^{[1
]}

Cai, Zixing ^{[2
]}

Yu, Jinxia ^{[3
]}

机构：

[1] Shaoguan Univ, Sch Comp Sci, Shaoguan 512005, Peoples R China

[2] Cent South Univ Changsha, Sch Informat Sci & Engn, Changsha 410083, Peoples R China

[3] Henan Politech Univ, Dept Comp Sci & Technol, Jiaozuo 454003, Peoples R China

来源：

CCDC 2009: 21ST CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, PROCEEDINGS | 2009年

关键词：

Object tracking; Particle Filter; Occlusion detection; Occlusion Recovery; Adaptive;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

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.

引用

页码：466 / +

页数：2

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