TAILIEUCHUNG - Báo cáo sinh học: " Research Article A Hierarchical Estimator for Object Tracking"

Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học Journal of Biology đề tài:Research Article A Hierarchical Estimator for Object Tracking | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010 Article ID 592960 11 pages doi 2010 592960 Research Article A Hierarchical Estimator for Object Tracking Chin-Wen Wu 1 Yi-Nung Chung 2 and Pau-Choo Chung1 1 Department of Electrical Engineering Institute of Computer and Communication Engineering National Cheng Kung University Tainan 701 Taiwan 2 Department of Electrical Engineering National Changhua University of Education Changhua 500 Taiwan Correspondence should be addressed to Yi-Nung Chung ynchung@ Received 17 November 2009 Revised 27 March 2010 Accepted 14 May 2010 Academic Editor Hsu-Yung Cheng Copyright 2010 Chin-Wen Wu et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 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. 1. Introduction Visual object tracking is an important issue in computer vision. It has applications in many fields including visual surveillance

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