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Boosting Local Shape Matching for Dense 3D Face Correspondence
Fan, Zhenfeng1,2; Hu, Xiyuan,1,2; Chen, Chen1,2; Peng, Silong1,2,3
2019-06
Conference NameIEEE Conference on Computer Vision and Pattern Recognition
Pages10944-10954
Conference DateJUN 16-20, 2019
Conference PlaceLong Beach, CA
PublisherIEEE
Contribution Rank1
Abstract

Dense 3D face correspondence is a fundamental and challenging issue in the literature of 3D face analysis. Correspondence between two 3D faces can be viewed as a nonrigid registration problem that one deforms into the other, which is commonly guided by a few facial landmarks in many existing works. However, the current works seldom consider the problem of incoherent deformation caused by landmarks. In this paper, we explicitly formulate the deformation as locally rigid motions guided by some seed points, and the formulated deformation satisfies coherent local motions everywhere on a face. The seed points are initialized by a few landmarks, and are then augmented to boost shape matching between the template and the target face step by step, to finally achieve dense correspondence. In each step, we employ a hierarchical scheme for local shape registration, together with a Gaussian reweighting strategy for accurate matching of local features around the seed points. In our experiments, we evaluate the proposed method extensively on several datasets, including two publicly available ones: FRGC v2.0 and BU-3DFE. The experimental results demonstrate that our method can achieve accurate feature correspondence, coherent local shape motion, and compact data representation. These merits actually settle some important issues for practical applications, such as expressions, noise, and partial data.
 

Keyword3D Face Dense correspondence
Subject Area人工智能
DOI10.1109/CVPR.2019.01120
URL查看原文
Indexed ByEI
Funding ProjectOpen Project of National Engineering Laboratory for Forensic Science of China[2017NELKFKT02] ; National Key R&D Program of China[2017YFC0803505] ; National Key R&D Program of China[2017YFC0803505] ; Open Project of National Engineering Laboratory for Forensic Science of China[2017NELKFKT02]
Language英语
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/26222
Collection智能制造技术与系统研究中心_多维数据分析
智能制造技术与系统研究中心
个人空间
Corresponding AuthorHu, Xiyuan,
Affiliation1.Institute of Automation, Chinese Academy of Sciences
2.University of Chinese Academy of Sciences
3.Beijing Visytem Co. Ltd.
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Fan, Zhenfeng,Hu, Xiyuan,,Chen, Chen,et al. Boosting Local Shape Matching for Dense 3D Face Correspondence[C]:IEEE,2019:10944-10954.
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