文献详情
SALIENCY OPTIMIZATION BASED ON COMPACTNESS AND BACKGROUND-PRIOR
文献类型会议
作者Zheng, Yu[1];Li, Lu[2];Bai, Xiangzhi[3];Zhou, Fugen[4]
机构
2016
会议论文集2016 INTERNATIONAL CONFERENCE ON DIGITAL IMAGE COM
通讯作者Li, L (reprint author), Beihang Univ, Image Proc Ctr, Beijing 100191, Peoples R China.
会议名称International Conference on Digital Image Computing - Techniques and Applications (DICTA)
页码范围87-92
来源信息年:2016  页码范围:87-92  
关键词saliency detection; foreground compactness; background prior; center prior
摘要Saliency detection has drawn increasing attention in the communities of computer vision and image processing. Recently, foreground compactness and background prior have been developed to enhance saliency detection. In this paper, we propose an effective saliency optimization scheme taking account the foreground compactness and background prior. First, a foreground compactness-based saliency detection algorithm is introduced, which integrates the center contrast and the compactness-fused representation of the Gaussian Mixture Models (GMMs)-decomposed soft abstraction. Second, a foreground-based background seeds selection algorithm is proposed to obtain the enhanced background prior based saliency, which can well alleviate the influence of the on-boundary objects to the final saliency in conventional background prior based saliency algorithms. At last, the problem of compactness and background prior-based saliency integration is formulated as a multi-objective optimization problem to obtain the optimal saliency. Extensive experiments on ASD and MSRA10K database demonstrate that the proposed method outperforms the state-of-the -art saliency detection methods.
收录情况EI(20170503318477)  CPCI-S(WOS:000391534900014)  
所属部门宇航学院
DOI号10.1109/DICTA.2016.7797079
会议地点Gold Coast, AUSTRALIA
会议开始日期2016-11-30
被引频次11
语言外文
人气指数718
浏览次数718
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