A hierarchical estimator for object tracking

Yi Nung Chung, Chin Wen Wu, Pau-Choo Chung

Research output: Contribution to journalArticle

2 Citations (Scopus)

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.

Original languageEnglish
Article number592960
JournalEurasip Journal on Advances in Signal Processing
Volume2010
DOIs
Publication statusPublished - 2010 Sep 24

Fingerprint

Kalman filters
Data fusion
Cameras
Computer simulation
Compensation and Redress

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Electrical and Electronic Engineering

Cite this

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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.",
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A hierarchical estimator for object tracking. / Chung, Yi Nung; Wu, Chin Wen; Chung, Pau-Choo.

In: Eurasip Journal on Advances in Signal Processing, Vol. 2010, 592960, 24.09.2010.

Research output: Contribution to journalArticle

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