Saliency Detection via Low-rank Reconstruction from Global to Local

IR > 新能源学院

	Saliency Detection via Low-rank Reconstruction from Global to Local
	Li, Ce1,2 ; Hu, Zhijia 1; Xiao, Limei1 ; Pan, Zhengrong1
	2015
会议名称	2015 CHINESE AUTOMATION CONGRESS (CAC)
会议录名称	2015 CHINESE AUTOMATION CONGRESS (CAC)
页码	669-673
出版地	345 E 47TH ST, NEW YORK, NY 10017 USA
出版者	IEEE
摘要	Saliency detection can be a useful technique for image semantic analysis such as auto image segmentation, image resize, advertising design and image compression. It is a core problem of saliency computing how to obtain the effective salient object with less non-saliency information, which is consist with movement of eye fixation. In this paper, we propose a saliency computing model based on rank-sparsity decomposition. In order to highlight saliency objects, the model eliminates the non-saliency background information from global to local. In an image, the salient object often has more strong contrast or difference relative to in the background. Firstly, with simple contrast in CIELab color space, we can obtain preliminary map. Secondly, using Low-rank reconstruction in global image, positioned roughly salient object. Finally, in order to eliminate nonsignificant noise, the mode reconstructs the redundant background from the block in the image. The experimental result shows that the proposed method can get a better saliency map compared with the-state-of-arts.
关键词	Visual saliency Saliency detection Clutter background Rank-sparsity
收录类别	CPCI
语种	英语
WOS研究方向	Automation & Control Systems ; Engineering
WOS类目	Automation & Control Systems ; Engineering, Electrical & Electronic
WOS记录号	WOS:000380546900124
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	会议论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/36527
专题	新能源学院电气工程与信息工程学院
通讯作者	Li, Ce
作者单位	1.Lanzhou Univ Technol, Coll Elect & Informat Engn, Lanzhou 730050, Peoples R China 2.Xi An Jiao Tong Univ, Elect & Informat Engn Sch, Xian 710049, Peoples R China
第一作者单位	电气工程与信息工程学院
通讯作者单位	电气工程与信息工程学院
推荐引用方式 GB/T 7714	Li, Ce,Hu, Zhijia,Xiao, Limei,et al. Saliency Detection via Low-rank Reconstruction from Global to Local[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2015:669-673.