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Enhanced Figure-Ground Classification With Background Prior Propagation
Chen, Yisong ; Chan, Antoni B.
刊名ieee transactions on image processing
2015
关键词Image segmentation multiple hypotheses fusion similarity voting IMAGE SEGMENTATION GRAPH CUTS EXTRACTION
DOI10.1109/TIP.2015.2389612
英文摘要We present an adaptive figure-ground segmentation algorithm that is capable of extracting foreground objects in a generic environment. Starting from an interactively assigned background mask, an initial background prior is defined and multiple soft-label partitions are generated from different foreground priors by progressive patch merging. These partitions are fused to produce a foreground probability map. The probability map is then binarized via threshold sweeping to create multiple hard-label candidates. A set of segmentation hypotheses is formed using different evaluation scores. From this set, the hypothesis with maximal local stability is propagated as the new background prior, and the segmentation process is repeated until convergence. Similarity voting is used to select a winner set, and the corresponding hypotheses are fused to yield the final segmentation result. Experiments indicate that our method performs at or above the current state-of-the-art on several data sets, with particular success on challenging scenes that contain irregular or multiple-connected foregrounds.; Computer Science, Artificial Intelligence; Engineering, Electrical & Electronic; SCI(E); EI; 0; ARTICLE; chenyisong@pku.edu.cn; abchan@cityu.edu.hk; 3; 873-885; 24
语种英语
内容类型期刊论文
源URL[http://ir.pku.edu.cn/handle/20.500.11897/151921]  
专题工学院
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GB/T 7714
Chen, Yisong,Chan, Antoni B.. Enhanced Figure-Ground Classification With Background Prior Propagation[J]. ieee transactions on image processing,2015.
APA Chen, Yisong,&Chan, Antoni B..(2015).Enhanced Figure-Ground Classification With Background Prior Propagation.ieee transactions on image processing.
MLA Chen, Yisong,et al."Enhanced Figure-Ground Classification With Background Prior Propagation".ieee transactions on image processing (2015).
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