Wei Wang, Ching and Hunter, Andrew (2010) Robust pose recognition of the obscured human body. International Journal of Computer Vision, 90 (3). pp. 313-330. ISSN 0920-5691

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Abstract

This paper presents a robust automated noninvasive video monitoring approach to recover the human pose in conditions with persistent heavy obscuration. The proposed methods are compared with Ramanan’s stylized pose detection method and Wang’s sequential pose model. The experimental results show that the proposed method performs significantly better than Ramanan’s approach, is able to estimate the obscured body pose with various postures and obscuration levels in different environments, and is not sensitive to illumination changes. The system is evaluated in two domains: sleeping human subjects obscured by a bed cover, and pedestrians with a cluttered background scene, low feature contrast and baggy clothing. The body part detectors are trained in the sleep monitoring domain but are still able to estimate the pose in the pedestrian domain, demonstrating the robustness of the proposed technique.

Item Type:	Article
Keywords:	Robust Pose Recognition, ref11, refdoi
Subjects:	G Mathematical and Computer Sciences > G400 Computer Science
Divisions:	College of Sciences > Faculty of Science > Lincoln School of Computer Science
Depositing User:	Rosaline Smith
Date Deposited:	09 Jul 2010 12:55
Last Modified:	15 May 2013 10:05
URI:	http://eprints.lincoln.ac.uk/id/eprint/2752

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