Human posture tracking in a multi-camera environment

Luo Sun; Huijun Di; Linmi Tao; Guangyou Xu

Human posture tracking in a multi-camera environment

Luo Sun, Huijun Di, Linmi Tao, Guangyou Xu^*

^*Corresponding author for this work

Tsinghua University

Research output: Contribution to journal › Article › peer-review

Abstract

Human posture tracking has long been of interest for its wide applications in human motion recognition and analysis. A tracking algorithm was developed using the Ω-shaped curve of the human head and shoulder as the tracking target based on the position and shape constraints among distinct views in a multi-camera environment. The algorithm integrates tracking and detection to simultaneously track the human posture and location in 3-D space as well as the head-shoulder contour. The robustness and efficacy of the approach is confirmed in challenging real-world scenarios.

Original language	English
Pages (from-to)	966-971
Number of pages	6
Journal	Qinghua Daxue Xuebao/Journal of Tsinghua University
Volume	51
Issue number	7
Publication status	Published - Jul 2011
Externally published	Yes

Keywords

Dynamic Bayesian network
Multi-camera
Particle filter
Posture tracking

Cite this

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AU - Tao, Linmi

AU - Xu, Guangyou

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AB - Human posture tracking has long been of interest for its wide applications in human motion recognition and analysis. A tracking algorithm was developed using the Ω-shaped curve of the human head and shoulder as the tracking target based on the position and shape constraints among distinct views in a multi-camera environment. The algorithm integrates tracking and detection to simultaneously track the human posture and location in 3-D space as well as the head-shoulder contour. The robustness and efficacy of the approach is confirmed in challenging real-world scenarios.

KW - Dynamic Bayesian network

KW - Multi-camera

KW - Particle filter

KW - Posture tracking

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Human posture tracking in a multi-camera environment

Abstract

Keywords

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