Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/33671
Title: Arbitrary body segmentation in static images
Authors: Li, S
Lu, H
Zhang, L 
Keywords: ℓ 1 based graph cuts
Pictorial structure
Superpixel based EM algorithm
Issue Date: 2012
Publisher: Elsevier
Source: Pattern recognition, 2012, v. 45, no. 9, p. 3402-3413 How to cite?
Journal: Pattern recognition 
Abstract: In this paper, a novel method for segmenting arbitrary human body in static images is proposed. With the body probability map obtained by the pictorial structure model, we develop a superpixel based EM-like algorithm to refine the map, which can then serve as the seeds of graph cuts optimization. To better obtain the final segmentation, we propose a novel ℓ 1 based graph cuts algorithm, which uses the sparse coding to construct the initialized graph and calculates the terminal links (t-links) and neighborhood links (n-links) simultaneously from the constructed graph. By employing this ℓ 1 based graph cuts, we can effectively and efficiently segment the human body from static images. The experiments on the publicly available challenging datasets demonstrate that our method outperforms many state-of-the-art methods on human body segmentation.
URI: http://hdl.handle.net/10397/33671
ISSN: 0031-3203
EISSN: 1873-5142
DOI: 10.1016/j.patcog.2012.03.011
Appears in Collections:Conference Paper

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

9
Last Week
0
Last month
1
Citations as of Aug 17, 2017

WEB OF SCIENCETM
Citations

8
Last Week
0
Last month
0
Citations as of Aug 13, 2017

Page view(s)

57
Last Week
1
Last month
Checked on Aug 13, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.