Saliency Density and Edge Response Based Salient Object Detection

Huiyun JING  Qi HAN  Xin HE  Xiamu NIU  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E96-D   No.5   pp.1243-1246
Publication Date: 2013/05/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E96.D.1243
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Image Recognition, Computer Vision
Keyword: 
salient object detection,  maximum saliency density and edge response,  branch-and-bound search,  

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Summary: 
We propose a novel threshold-free salient object detection approach which integrates both saliency density and edge response. The salient object with a well-defined boundary can be automatically detected by our approach. Saliency density and edge response maximization is used as the quality function to direct the salient object discovery. The global optimal window containing a salient object is efficiently located through the proposed saliency density and edge response based branch-and-bound search. To extract the salient object with a well-defined boundary, the GrabCut method is applied, initialized by the located window. Experimental results show that our approach outperforms the methods only using saliency or edge response and achieves a comparable performance with the best state-of-the-art method, while being without any threshold or multiple iterations of GrabCut.