A Hierarchical Estimator for Object Tracking

A closed-loop local-global integrated hierarchical estimator (CLGIHE) approach for object tracking using multiple cameras is proposed. The Kalman filter is used in both the local and global estimates. In contrast to existing approaches where the local and global estimations are performed independent...

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Bibliographic Details
Published in:EURASIP journal on advances in signal processing 2010-01, Vol.2010 (1), Article 592960
Main Authors: Wu, Chin-Wen, Chung, Yi-Nung, Chung, Pau-Choo
Format: Article
Language:English
Subjects:
Cameras
Compensation
Data integration
Engineering
Estimates
Estimators
Gain
Optimization
Quantum Information Technology
Research Article
Signal,Image and Speech Processing
Spintronics
Tracking
Video Analysis for Human Behavior Understanding
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Summary:A closed-loop local-global integrated hierarchical estimator (CLGIHE) approach for object tracking using multiple cameras is proposed. The Kalman filter is used in both the local and global estimates. In contrast to existing approaches where the local and global estimations are performed independently, the proposed approach combines local and global estimates into one for mutual compensation. Consequently, the Kalman-filter-based data fusion optimally adjusts the fusion gain based on environment conditions derived from each local estimator. The global estimation outputs are included in the local estimation process. Closed-loop mutual compensation between the local and global estimations is thus achieved to obtain higher tracking accuracy. A set of image sequences from multiple views are applied to evaluate performance. Computer simulation and experimental results indicate that the proposed approach successfully tracks objects.
ISSN:1687-6180
1687-6172
1687-6180
DOI:10.1155/2010/592960