中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Salient Object Detection via Random Forest

文献类型:期刊论文

作者Shuze Du; Shifeng Chen
刊名IEEE SIGNAL PROCESSING LETTERS
出版日期2014
英文摘要Salient object detection plays an important role in image pre-processing. Existing approaches often neglect the contours of salient objects, thus resulting in inaccurate detection for large objects. Besides, they mainly focus on detecting only a single object. In this paper, we detect the salient object from the view of the object contour. We propose to exploit the random forest to measure patch rarities and compute similarities among patches. A global rarity map is calculated based on the patch's rareness over the whole image. The approximate contour of the salient object is extracted based on this rarity map by using an active contour model. Next, a local saliency map is obtained by the similarities of patches inside the contour and those outside. Finally, the local map is refined through image segmentation. Our method can detect not only a single object but also multiple objects. Experimental evaluation on the ASD-1000 and SED2 datasets shows that our method outperforms the state-of-the-art methods.
收录类别SCI
原文出处http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6662451
语种英语
源URL[http://ir.siat.ac.cn:8080/handle/172644/5343]  
专题深圳先进技术研究院_集成所
作者单位IEEE SIGNAL PROCESSING LETTERS
推荐引用方式
GB/T 7714
Shuze Du,Shifeng Chen. Salient Object Detection via Random Forest[J]. IEEE SIGNAL PROCESSING LETTERS,2014.
APA Shuze Du,&Shifeng Chen.(2014).Salient Object Detection via Random Forest.IEEE SIGNAL PROCESSING LETTERS.
MLA Shuze Du,et al."Salient Object Detection via Random Forest".IEEE SIGNAL PROCESSING LETTERS (2014).

入库方式: OAI收割

来源:深圳先进技术研究院

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