Segmenting human from photo images based on a coarse-to-fine scheme

Lu, H. and Fang, G. and Shao, X. and Li, Xuelong (2012) Segmenting human from photo images based on a coarse-to-fine scheme. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 42 (3), pp. 889-899. ISSN 1083-4419.

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Official URL: http://dx.doi.org/10.1109/TSMCB.2011.2182048

Abstract

Human segmentation in photo images is a challenging and important problem that finds numerous applications ranging from album making and photo classification to image retrieval. Previous works on human segmentation usually demand a time-consuming training phase for complex shape-matching processes. In this paper, we propose a straightforward framework to automatically recover human bodies from color photos. Employing a coarse-to-fine strategy, we first detect a coarse torso (CT) using the multicue CT detection algorithm and then extract the accurate region of the upper body. Then, an iterative multiple oblique histogram algorithm is presented to accurately recover the lower body based on human kinematics. The performance of our algorithm is evaluated on our own data set (contains 197 images with human body region ground truth data), VOC 2006, and the 2010 data set. Experimental results demonstrate the merits of the proposed method in segmenting a person with various poses.

Metadata

Item Type:	Article
School:	Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
Depositing User:	Sarah Hall
Date Deposited:	07 Jun 2013 08:38
Last Modified:	09 Aug 2023 12:33
URI:	https://eprints.bbk.ac.uk/id/eprint/7353

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