Saliency Detection for Stereoscopic Images Based on Depth Confidence Analysis and Multiple Cues Fusion

doi:10.1109/LSP.2016.2557347

CORC > 计算技术研究所 > 中国科学院计算技术研究所 > 中国科学院计算技术研究所期刊论文 > 英文

	Saliency Detection for Stereoscopic Images Based on Depth Confidence Analysis and Multiple Cues Fusion
	Cong, Runmin 3; Lei, Jianjun 3; Zhang, Changqing 4; Huang, Qingming 1; Cao, Xiaochun 2; Hou, Chunping 3
刊名	IEEE SIGNAL PROCESSING LETTERS
	2016-06-01
卷号	23 期号:6 页码:5
关键词	Color and depth-based compactness depth confidence measure multiple cues saliency detection
ISSN号	1070-9908
DOI	10.1109/LSP.2016.2557347
英文摘要	Stereoscopic perception is an important part of human visual system that allows the brain to perceive depth. However, depth information has not been well explored in existing saliency detection models. In this letter, a novel saliency detection method for stereoscopic images is proposed. First, we propose a measure to evaluate the reliability of depth map, and use it to reduce the influence of poor depth map on saliency detection. Then, the input image is represented as a graph, and the depth information is introduced into graph construction. After that, a new definition of compactness using color and depth cues is put forward to compute the compactness saliency map. In order to compensate the detection errors of compactness saliency when the salient regions have similar appearances with background, foreground saliency map is calculated based on depth-refined foreground seeds' selection (DRSS) mechanism and multiple cues contrast. Finally, these two saliency maps are integrated into a final saliency map through weighted-sum method according to their importance. Experiments on two publicly available stereo data sets demonstrate that the proposed method performs better than other ten state-of-the-art approaches.
资助项目	Natural Science Foundation of China[61271324] ; Natural Science Foundation of China[61520106002] ; Natural Science Foundation of China[61471262] ; Natural Science Foundation of China[91320201]
WOS研究方向	Engineering
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000391265400001
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/7732]
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Lei, Jianjun
作者单位	1.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Inst Informat Engn, Beijing 100093, Peoples R China 3.Tianjin Univ, Sch Elect Informat Engn, Tianjin 300072, Peoples R China 4.Tianjin Univ, Sch Comp Sci & Technol, Tianjin 300072, Peoples R China
推荐引用方式 GB/T 7714	Cong, Runmin,Lei, Jianjun,Zhang, Changqing,et al. Saliency Detection for Stereoscopic Images Based on Depth Confidence Analysis and Multiple Cues Fusion[J]. IEEE SIGNAL PROCESSING LETTERS,2016,23(6):5.
APA	Cong, Runmin,Lei, Jianjun,Zhang, Changqing,Huang, Qingming,Cao, Xiaochun,&Hou, Chunping.(2016).Saliency Detection for Stereoscopic Images Based on Depth Confidence Analysis and Multiple Cues Fusion.IEEE SIGNAL PROCESSING LETTERS,23(6),5.
MLA	Cong, Runmin,et al."Saliency Detection for Stereoscopic Images Based on Depth Confidence Analysis and Multiple Cues Fusion".IEEE SIGNAL PROCESSING LETTERS 23.6(2016):5.