A Hierarchical Estimator for Object Tracking. (10th June 2010)

• Record Type: Journal Article
• Authors: Wu Wu, Chin-Wen Chin-Wen; Chung Chung, Yi-Nung Yi-Nung; Chung Chung, Pau-Choo Pau-Choo
• Other Names: Cheng Cheng Hsu-Yung Hsu-Yung Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2010(2010)
• Publication Date: 2010-06-10
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2010/592960
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : 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.