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A Visual-Attention Model Using Earth Mover’s Distance-Based Saliency Measurement and Nonlinear Feature Combination
Alternative Titlefb@cqu.edu.cn
Yuewei Lin1; Yuan Yan Tang2; Bin Fang3; Zhaowei Shang3; Yonghui Huang3; Song Wang1
2013-02
Source PublicationIEEE Transactions on Pattern Analysis and Machine Intelligence
ISSN0162-8828
Volume35Issue:2Pages:314 - 328
Abstract

This paper introduces a new computational visual-attention model for static and dynamic saliency maps. First, we use the Earth Mover's Distance (EMD) to measure the center-surround difference in the receptive field, instead of using the Difference-of-Gaussian filter that is widely used in many previous visual-attention models. Second, we propose to take two steps of biologically inspired nonlinear operations for combining different features: combining subsets of basic features into a set of super features using the Lm-norm and then combining the super features using the Winner-Take-All mechanism. Third, we extend the proposed model to construct dynamic saliency maps from videos by using EMD for computing the center-surround difference in the spatiotemporal receptive field. We evaluate the performance of the proposed model on both static image data and video data. Comparison results show that the proposed model outperforms several existing models under a unified evaluation setting. 

KeywordDynamic Saliency Maps Earth Mover's Distance (Emd) Saliency Maps Spatiotemporal Receptive Field (Strf) Visual Attention
DOIhttp://doi.org/10.1109/TPAMI.2012.119
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000312560600006
PublisherIEEE COMPUTER SOC, 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1314 USA
The Source to ArticleScopus
Fulltext Access
Citation statistics
Cited Times [WOS]:25   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorYuewei Lin; Yuan Yan Tang; Bin Fang; Zhaowei Shang; Yonghui Huang; Song Wang
Affiliation1.Department of Computer Science and Engineering, University of South Carolina, Columbia, SC 29208.
2.Department of Computer and Information Science, University of Macau, Macau and the College of Computer Science, Chongqing University, Chongqing 400030, China.
3.College of Computer Science, Chongqing University, Chongqing 400030, China
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Yuewei Lin,Yuan Yan Tang,Bin Fang,et al. A Visual-Attention Model Using Earth Mover’s Distance-Based Saliency Measurement and Nonlinear Feature Combination[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2013,35(2):314 - 328.
APA Yuewei Lin,Yuan Yan Tang,Bin Fang,Zhaowei Shang,Yonghui Huang,&Song Wang.(2013).A Visual-Attention Model Using Earth Mover’s Distance-Based Saliency Measurement and Nonlinear Feature Combination.IEEE Transactions on Pattern Analysis and Machine Intelligence,35(2),314 - 328.
MLA Yuewei Lin,et al."A Visual-Attention Model Using Earth Mover’s Distance-Based Saliency Measurement and Nonlinear Feature Combination".IEEE Transactions on Pattern Analysis and Machine Intelligence 35.2(2013):314 - 328.
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