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  2. 西安光学精密机械研究所
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  4. 光学影像学习与分析中心
Spatial-Aware Object-Level Saliency Prediction by Learning Graphlet Hierarchies

文献类型：期刊论文

作者Zhang, Luming1; Xia, Yingjie1,2; Ji, Rongrong3; Li, Xuelong4
刊名ieee transactions on industrial electronics
出版日期2015-02-01
卷号62期号:2页码:1301-1308
关键词Eye tracking graphlet object-level saliency spatial
英文摘要to fill the semantic gap between the predictive power of computational saliency models and human behavior, this paper proposes to predict where people look at using spatial-aware object-level cues. while object-level saliency has been recently suggested by psychophysics experiments and shown effective with a few computational models, the spatial relationship between the objects has not yet been explored in this context. we in this work for the first time explicitly model such spatial relationship, as well as leveraging semantic information of an image to enhance object-level saliency modeling. the core computational module is a graphlet-based (i.e., graphlets are moderate-sized connected subgraphs) deep architecture, which hierarchically learns a saliency map from raw image pixels to object-level graphlets (ogls) and further to spatial-level graphlets (sgls). eye tracking data are also used to leverage human experience in saliency prediction. experimental results demonstrate that the proposed ogls and sgls well capture object-level and spatial-level cues relating to saliency, and the resulting saliency model performs competitively compared with the state-of-the-art.
WOS标题词science & technology ; technology
类目[WOS]automation & control systems ; engineering, electrical & electronic ; instruments & instrumentation
研究领域[WOS]automation & control systems ; engineering ; instruments & instrumentation
关键词[WOS]image ; quantization ; search ; design
收录类别SCI ; EI
语种英语
WOS记录号WOS:000347799500062
公开日期2015-07-14
源URL[http://ir.opt.ac.cn/handle/181661/24090]  
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.Zhejiang Univ, Dept Comp Sci, Hangzhou 310027, Zhejiang, Peoples R China
2.Hangzhou Normal Univ, Hangzhou Inst Serv Engn, Hangzhou 310036, Zhejiang, Peoples R China
3.Xiamen Univ, Dept Cognit Sci, Sch Informat Sci & Engn, Xiamen 361005, Peoples R China
4.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Ctr OPT IMagery Anal & Learning, State Key Lab Transient Opt & Photon, Xian 710119, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Luming,Xia, Yingjie,Ji, Rongrong,et al. Spatial-Aware Object-Level Saliency Prediction by Learning Graphlet Hierarchies[J]. ieee transactions on industrial electronics,2015,62(2):1301-1308.
APA Zhang, Luming,Xia, Yingjie,Ji, Rongrong,&Li, Xuelong.(2015).Spatial-Aware Object-Level Saliency Prediction by Learning Graphlet Hierarchies.ieee transactions on industrial electronics,62(2),1301-1308.
MLA Zhang, Luming,et al."Spatial-Aware Object-Level Saliency Prediction by Learning Graphlet Hierarchies".ieee transactions on industrial electronics 62.2(2015):1301-1308.

入库方式： OAI收割

来源：西安光学精密机械研究所

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