UM
A Hybrid of Local and Global Saliencies for Detecting Image Salient Region and Appearance
Peng, Qinmu1; Cheung, Yiu-ming1,2; You, Xinge3; Tang, Yuan Yan4
2017-01
Source PublicationIEEE Transactions on Systems, Man, and Cybernetics: Systems
ABS Journal Level3
ISSN2168-2216
Volume47Issue:1Pages:86-97
Abstract

This paper presents a visual saliency detection approach, which is a hybrid of local feature-based saliency and global feature-based saliency (simply called local saliency and global saliency, respectively, for short). First, we propose an automatic selection of smoothing parameter scheme to make the foreground and background of an input image more homogeneous. Then, we partition the smoothed image into a set of regions and compute the local saliency by measuring the color and texture dissimilarity in the smoothed regions and the original regions, respectively. Furthermore, we utilize the global color distribution model embedded with color coherence, together with the multiple edge saliency, to yield the global saliency. Finally, we combine the local and global saliencies, and utilize the composition information to obtain the final saliency. Experimental results show the efficacy of the proposed method, featuring: 1) the enhanced accuracy of detecting visual salient region and appearance in comparison with the existing counterparts, 2) the robustness against the noise and the low-resolution problem of images, and 3) its applicability to multisaliency detection task.

KeywordGradient Minimization Multiple Salient Edges Saliency Detection Visual Attention
DOIhttps://doi.org/10.1109/TSMC.2016.2564922
URLView the original
Indexed BySCI
Language英语
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systems ; Computer Science, Cybernetics
WOS IDWOS:000391480400008
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
The Source to ArticleWOS
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Cited Times [WOS]:19   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Corresponding AuthorPeng, Qinmu; Cheung, Yiu-ming; You, Xinge; Tang, Yuan Yan
Affiliation1.Department of Computer Science, Hong Kong Baptist University, Hong Kong
2.United International College, Beijing Normal University–Hong Kong Baptist University, Zhuhai 519000, China
3.School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, China
4.Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Macau 999078, China
Corresponding Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Peng, Qinmu,Cheung, Yiu-ming,You, Xinge,et al. A Hybrid of Local and Global Saliencies for Detecting Image Salient Region and Appearance[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems,2017,47(1):86-97.
APA Peng, Qinmu,Cheung, Yiu-ming,You, Xinge,&Tang, Yuan Yan.(2017).A Hybrid of Local and Global Saliencies for Detecting Image Salient Region and Appearance.IEEE Transactions on Systems, Man, and Cybernetics: Systems,47(1),86-97.
MLA Peng, Qinmu,et al."A Hybrid of Local and Global Saliencies for Detecting Image Salient Region and Appearance".IEEE Transactions on Systems, Man, and Cybernetics: Systems 47.1(2017):86-97.
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