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Indexed by:期刊论文

Date of Publication:2014-09-01

Journal:Journal of Information and Computational Science

Included Journals:EI、Scopus

Volume:11

Issue:13

Page Number:4467-4476

ISSN No.:15487741

Abstract:Recent years saliency detection plays an important role in computer vision. In the paper, we present a bottom-up salient object detection method. First, we compute two complementary coarse saliency maps based on the dense and sparse reconstruction errors considering the boundary priors. Then we rank the coarse maps and integrate the ranking values in a multiplication way. Finally, we compute an exact saliency map which is robust to the images with cluttered background. Extensive experiments on two public available databases demonstrate the superiority of the proposed method compared to 12 state-the-of-art approaches. Copyright ? 2014 Binary Information Press.