Visual saliency detection using information divergence
文献类型：期刊论文
| 作者 | Hou, Weilong1; Gao, Xinbo1; Tao, Dacheng2,3 ; Li, Xuelong4
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| 刊名 | pattern recognition
 |
| 出版日期 | 2013-10-01 |
| 卷号 | 46期号:10页码:2658-2669 |
| 关键词 | Visual attention Saliency detection Independent component analysis Bayesian surprise model |
| 英文摘要 | the technique of visual saliency detection supports video surveillance systems by reducing redundant information and highlighting the critical, visually important regions. it follows that information about the image might be of great importance in depicting the visual saliency. however, the majority of existing methods extract contrast-like features without considering the contribution of information content. based on the hypothesis that information divergence leads to visual saliency, a two-stage framework for saliency detection, namely information divergence model (idm), is introduced in this paper. the term "information divergence" is used to express the non-uniform distribution of the visual information in an image. the first stage is constructed to extract sparse features by employing independent component analysis (ica) and difference of gaussians (dog) filter. the second stage improves the bayesian surprise model to compute information divergence across an image. a visual saliency map is finally obtained from the information divergence. experiments are conducted on nature image databases, psychological patterns and video surveillance sequences. the results show the effectiveness of the proposed method by comparing it with 13 state-of-the-art visual saliency detection methods. (c) 2013 elsevier ltd. all rights reserved. |
| WOS标题词 | science & technology ; technology |
| 类目[WOS] | computer science, artificial intelligence ; engineering, electrical & electronic |
| 研究领域[WOS] | computer science ; engineering |
| 关键词[WOS] | sparse representation ; neurobiological model ; image retrieval ; natural scenes ; simple cells ; attention ; features ; filters ; overt ; recognition |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:000320477400005 |
| 公开日期 | 2015-06-30 |
| 源URL | [http://ir.opt.ac.cn/handle/181661/23444]  |
| 专题 | 西安光学精密机械研究所_光学影像学习与分析中心 |
| 作者单位 | 1.Xidian Univ, Sch Elect Engn, Xian 710071, Shaanxi, Peoples R China 2.Univ Technol Sydney, Ctr Quantum Computat & Intelligent Syst, Ultimo, NSW 2007, Australia 3.Univ Technol Sydney, Fac Engn & Informat Technol, Ultimo, NSW 2007, Australia 4.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Ctr Opt Imagery Anal & Learning OPTIMAL, State Key Lab Transient Opt & Photon, Xian 710119, Shaanxi, Peoples R China |
| 推荐引用方式 GB/T 7714 | Hou, Weilong,Gao, Xinbo,Tao, Dacheng,et al. Visual saliency detection using information divergence[J]. pattern recognition,2013,46(10):2658-2669. |
| APA | Hou, Weilong,Gao, Xinbo,Tao, Dacheng,&Li, Xuelong.(2013).Visual saliency detection using information divergence.pattern recognition,46(10),2658-2669. |
| MLA | Hou, Weilong,et al."Visual saliency detection using information divergence".pattern recognition 46.10(2013):2658-2669. |
入库方式： OAI收割
来源：西安光学精密机械研究所
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