Computer Science ›› 2017, Vol. 44 ›› Issue (11): 314-319.doi: 10.11896/j.issn.1002-137X.2017.11.048

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Co-saliency Detection via Superpixel Matching

ZHANG Zhao-feng, WU Ze-min, JIANG Qing-zhu, DU Lin and HU Lei   

  • Online:2018-12-01 Published:2018-12-01

Abstract: To effectively address the issue of multi-scene co-saliency detection,we proposed a novel model based on superpixel matching and cellular automata.First of all,we introduced an adjacent superpixel sets matching algorithm based on Hausdorff distance to achieve exact matching between image supperpixels.Comparing to the traditional superpixel matching algorithm,the new algorithm greatly improves the matching accuracy.In addition,we further proposed the 2-layer cellular automata via intra image and inter images to carry out the significant propagation of multiple images,thus exploit the intrinsic relevance of similar regions through interactions with neighbors in multi-scene.Experimental results demonstrate that our model outperforms state-of-the-art methods.Furthermore,the proposed methods is efficient and robust.

Key words: Co-saliency detection,Hausdorff distance,Superpixel matching,Cellular automata,Saliency propagation

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