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

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 adapt...

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Bibliographic Details
Published in2009 Chinese Control and Decision Conference pp. 466 - 469
Main Authors Zhuohua Duan, Zixing Cai, Jinxia Yu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2009
Subjects
Adaptive
Computer science
Filtering
Noise measurement
Object detection
Object tracking
Occlusion detection
Occlusion Recovery
Particle Filter
Particle filters
Particle measurements
Particle tracking
Robustness
Target tracking
Time measurement
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Summary: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.
ISBN:9781424427222
1424427223
ISSN:1948-9439
1948-9447
DOI:10.1109/CCDC.2009.5195009