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Focusness guided salient object detection
Xiao Xiaolin; Zhou Yicong
2017-11-27
Conference NameIEEE International Conference on Systems, Man, and Cybernetics (SMC)
Source Publication2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
Volume2017-January
Pages3462-3466
Conference DateOCT 05-08, 2017
Conference PlaceBanff, CANADA
Abstract

Salient object detection aims to correctly highlight the most salient object(s) in an image. Combining fine-grained contrast prior with rough-grained object consistency, this paper proposes a Focusness Guided Salient object detection (FGS) algorithm. To obtain clean and precise contrast map, FGS uses the focusness prior to guide the contrast map. Combing different saliency priors, FGS utilizes a unified least-square framework to generate the final optimal salient map. Experiments demonstrate the proposed method outperforms the state-of-the-arts.

DOI10.1109/SMC.2017.8123166
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS IDWOS:000427598703089
Scopus ID2-s2.0-85044356323
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Citation statistics
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Faculty of Science and Technology
AffiliationUniversity of Macau
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Xiao Xiaolin,Zhou Yicong. Focusness guided salient object detection[C], 2017, 3462-3466.
APA Xiao Xiaolin., & Zhou Yicong (2017). Focusness guided salient object detection. 2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017, 2017-January, 3462-3466.
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