OPT OpenIR  > 光谱成像技术研究室
Visual saliency detection using information divergence
Hou, Weilong1; Gao, Xinbo1; Tao, Dacheng2,3; Li, Xuelong4
2013-10-01
发表期刊PATTERN RECOGNITION
卷号46期号:10页码:2658-2669
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.
文章类型Article
关键词Visual Attention Saliency Detection Independent Component Analysis Bayesian Surprise Model
WOS标题词Science & Technology ; Technology
DOI10.1016/j.patcog.2013.03.008
收录类别SCI ; EI
关键词[WOS]SPARSE REPRESENTATION ; NEUROBIOLOGICAL MODEL ; IMAGE RETRIEVAL ; NATURAL SCENES ; SIMPLE CELLS ; ATTENTION ; FEATURES ; FILTERS ; OVERT ; RECOGNITION
语种英语
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号WOS:000320477400005
引用统计
被引频次:33[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.opt.ac.cn/handle/181661/23444
专题光谱成像技术研究室
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.
条目包含的文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
Visual saliency dete(8294KB)期刊论文出版稿限制开放CC BY请求全文
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Hou, Weilong]的文章
[Gao, Xinbo]的文章
[Tao, Dacheng]的文章
百度学术
百度学术中相似的文章
[Hou, Weilong]的文章
[Gao, Xinbo]的文章
[Tao, Dacheng]的文章
必应学术
必应学术中相似的文章
[Hou, Weilong]的文章
[Gao, Xinbo]的文章
[Tao, Dacheng]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。