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Conference Paper: Accurate foreground segmentation without pre-learning

TitleAccurate foreground segmentation without pre-learning
Authors
KeywordsSegmentation
Contrast attenuation
Foreground segmentation
Graph cut
Automatic algorithms
Issue Date2011
PublisherIEEE Computer Society. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1001790
Citation
The 6th International Conference on Image and Graphics (ICIG 2011), Hefei, Anhui, China, 12-15 August 2011. In Proceedings of the 6th ICIG, 2011, p. 331-337 How to Cite?
AbstractForeground segmentation has been widely used in many computer vision applications. However, most of the existing methods rely on a pre-learned motion or background model, which will increase the burden of users. In this paper, we present an automatic algorithm without pre-learning for segmenting foreground from background based on the fusion of motion, color and contrast information. Motion information is enhanced by a novel method called support edges diffusion (SED) , which is built upon a key observation that edges of the difference image of two adjacent frames only appear in moving regions in most of the cases. Contrasts in background are attenuated while those in foreground are enhanced using gradient of the previous frame and that of the temporal difference. Experiments on many video sequences demonstrate the effectiveness and accuracy of the proposed algorithm. The segmentation results are comparable to those obtained by other state-of-the-art methods that depend on a pre-learned background or a stereo setup. © 2011 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/137652
ISBN
References

 

DC FieldValueLanguage
dc.contributor.authorKuang, Zen_HK
dc.contributor.authorZhou, Hen_HK
dc.contributor.authorWong, KKYen_HK
dc.date.accessioned2011-08-26T14:30:33Z-
dc.date.available2011-08-26T14:30:33Z-
dc.date.issued2011en_HK
dc.identifier.citationThe 6th International Conference on Image and Graphics (ICIG 2011), Hefei, Anhui, China, 12-15 August 2011. In Proceedings of the 6th ICIG, 2011, p. 331-337en_HK
dc.identifier.isbn978-0-7695-4541-7-
dc.identifier.urihttp://hdl.handle.net/10722/137652-
dc.description.abstractForeground segmentation has been widely used in many computer vision applications. However, most of the existing methods rely on a pre-learned motion or background model, which will increase the burden of users. In this paper, we present an automatic algorithm without pre-learning for segmenting foreground from background based on the fusion of motion, color and contrast information. Motion information is enhanced by a novel method called support edges diffusion (SED) , which is built upon a key observation that edges of the difference image of two adjacent frames only appear in moving regions in most of the cases. Contrasts in background are attenuated while those in foreground are enhanced using gradient of the previous frame and that of the temporal difference. Experiments on many video sequences demonstrate the effectiveness and accuracy of the proposed algorithm. The segmentation results are comparable to those obtained by other state-of-the-art methods that depend on a pre-learned background or a stereo setup. © 2011 IEEE.en_HK
dc.languageengen_US
dc.publisherIEEE Computer Society. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1001790-
dc.relation.ispartofInternational Conference on Image and Graphics Proceedingsen_HK
dc.rightsInternational Conference on Image and Graphics Proceedings. Copyright © IEEE Computer Society.-
dc.rights©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectSegmentationen_HK
dc.subjectContrast attenuationen_HK
dc.subjectForeground segmentationen_HK
dc.subjectGraph cut-
dc.subjectAutomatic algorithms-
dc.titleAccurate foreground segmentation without pre-learningen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailKuang, Z: zhkuang@cs.hku.hken_HK
dc.identifier.emailZhou, H: hzhou@cs.hku.hk-
dc.identifier.emailWong, KKY: kykwong@cs.hku.hk-
dc.identifier.authorityWong, KKY=rp01393en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/ICIG.2011.150en_HK
dc.identifier.scopuseid_2-s2.0-80052995268en_HK
dc.identifier.hkuros191682en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-80052995268&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage331en_HK
dc.identifier.epage337en_HK
dc.publisher.placeUnited States-
dc.description.otherThe 6th International Conference on Image and Graphics (ICIG 2011), Hefei, Anhui, China, 12-15 August 2011. In Proceedings of the 6th ICIG, 2011, p. 331-337-
dc.identifier.scopusauthoridWong, KYK=24402187900en_HK
dc.identifier.scopusauthoridZhou, H=50862367900en_HK
dc.identifier.scopusauthoridKuang, Z=7005702727en_HK

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