FINE-STRUCTURED OBJECT SEGMENTATION VIA LOCAL AND NONLOCAL NEIGHBORHOOD PROPAGATION

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 先进时空数据分析与学习

	FINE-STRUCTURED OBJECT SEGMENTATION VIA LOCAL AND NONLOCAL NEIGHBORHOOD PROPAGATION
	Gong, Yongchao; Xiang, Shiming; Wang, Lingfeng; Pan, Chunhong
	2015-09
会议名称	IEEE International Conference on Image Processing
页码	4619-4623
会议日期	2015-9-27 ~ 2015-9-30
会议地点	Québec City, Canada
摘要	In this paper, we present a novel method for the challenging task of fine-structured (FS) object segmentation. This task is formulated as a label propagation problem on an affinity graph. To enhance the completeness and connectivity of the FS objects, we introduce a novel neighborhood system combining both local and nonlocal connections, together with a robust scheme for edge weight calculation. Additionally, region cost is incorporated into the energy function to further maintain the connectivity of fine parts where the propagation is hard to reach. An appealing advantage of the proposed method is that the energy minimization has a closed-form solution and global optimum is guaranteed. Comparative experimental results on three datasets demonstrate the effectiveness of the proposed method.
关键词	Fine-structured (Fs) Object Segmentation Affinity Graph Local And nonLocal Neighborhood System Region Cost Closed-form Solution
收录类别	EI
语种	英语
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/14489
专题	多模态人工智能系统全国重点实验室_先进时空数据分析与学习
作者单位	National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences
第一作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Gong, Yongchao,Xiang, Shiming,Wang, Lingfeng,et al. FINE-STRUCTURED OBJECT SEGMENTATION VIA LOCAL AND NONLOCAL NEIGHBORHOOD PROPAGATION[C],2015:4619-4623.

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