PM-PM: PatchMatch With Potts Model for Object Segmentation and Stereo Matching

	PM-PM: PatchMatch With Potts Model for Object Segmentation and Stereo Matching
	Xu, Shibiao1,2 ; Zhang, Feihu 2; He, Xiaofei 3; Shen, Xukun 1; Zhang, Xiaopeng2
发表期刊	IEEE TRANSACTIONS ON IMAGE PROCESSING
	2015-03-25
卷号	24 期号:7 页码:2182-2196
文章类型	Article
摘要	This paper presents a unified variational formulation for joint object segmentation and stereo matching, which takes both accuracy and efficiency into account. In our approach, depth-map consists of compact objects, each object is represented through three different aspects: 1) the perimeter in image space; 2) the slanted object depth plane; and 3) the planar bias, which is to add an additional level of detail on top of each object plane in order to model depth variations within an object. Compared with traditional high quality solving methods in low level, we use a convex formulation of the multilabel Potts Model with PatchMatch stereo techniques to generate depth-map at each image in object level and show that accurate multiple view reconstruction can be achieved with our formulation by means of induced homography without discretization or staircasing artifacts. Our model is formulated as an energy minimization that is optimized via a fast primal-dual algorithm, which can handle several hundred object depth segments efficiently. Performance evaluations in the Middlebury benchmark data sets show that our method outperforms the traditional integer-valued disparity strategy as well as the original PatchMatch algorithm and its variants in subpixel accurate disparity estimation. The proposed algorithm is also evaluated and shown to produce consistently good results for various real-world data sets (KITTI benchmark data sets and multiview benchmark data sets).
关键词	Object Segmentation Stereo Matching Potts Model Patchmatch Multiple View Reconstruction
WOS标题词	Science & Technology ; Technology
关键词[WOS]	CORRESPONDENCE FIELD ESTIMATION ; BELIEF PROPAGATION ; IMAGE SEGMENTATION ; GRAPH CUTS ; COST AGGREGATION ; OPTIMIZATION ; MINIMIZATION ; ALGORITHMS ; SEARCH ; COLOR
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:000352732800006
引用统计	被引频次：55[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/8106
专题	多模态人工智能系统全国重点实验室_多媒体计算
作者单位	1.Beihang Univ, State Key Lab Virtual Real Technol & Syst, Beijing 100191, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 3.Zhejiang Univ, Coll Comp Sci, Hangzhou 310027, Zhejiang, Peoples R China
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	Xu, Shibiao,Zhang, Feihu,He, Xiaofei,et al. PM-PM: PatchMatch With Potts Model for Object Segmentation and Stereo Matching[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2015,24(7):2182-2196.
APA	Xu, Shibiao,Zhang, Feihu,He, Xiaofei,Shen, Xukun,&Zhang, Xiaopeng.(2015).PM-PM: PatchMatch With Potts Model for Object Segmentation and Stereo Matching.IEEE TRANSACTIONS ON IMAGE PROCESSING,24(7),2182-2196.
MLA	Xu, Shibiao,et al."PM-PM: PatchMatch With Potts Model for Object Segmentation and Stereo Matching".IEEE TRANSACTIONS ON IMAGE PROCESSING 24.7(2015):2182-2196.

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