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Exploring generalized shape analysis by topological representations
Zhou, Zhen; Huang, Yongzhen; Wang, Liang; Tan, Tieniu
Source PublicationPATTERN RECOGNITION LETTERS
2017-02-01
Volume87Issue:87Pages:177-185
SubtypeArticle
AbstractOne of the most common properties of various data in pattern recognition is the shape, and the shape matters. However, the shape can appear with uncertain appearances, e.g., the shapes of a person in different poses. We realize that the most fundamental feature of any shape is the number of connected components, the number of holes and its higher dimensional counterparts. These are what we call topological invariants. This is the place where topology comes into play for pattern recognition. Persistent homology, one of the most powerful tools in algebraic topology, is proposed to compute these topological invariants at different resolutions. The proposed method, by firstly transferring the given data into a topological graph representation, i.e., the simplicial complex, can assemble discrete points into a global structure. Then by integrating with multiple filtrations and metric learning, both the global structure and different local parts can be taken into account at the same time. We test the proposed method in 21) shape classification, 2.5D gait identification and 3D facial expression recognition. Experimental results demonstrate the effectiveness of this generalized shape analysis method and show its potentials in different applications. Moreover, we provide a new insight for the generalized shape analysis. (C) 2016 Elsevier B.V. All rights reserved.
KeywordTopology Persistent Homology Shape Analysis Gait Recognition 3d Facial Expression Recognition
WOS HeadingsScience & Technology ; Technology
DOI10.1016/j.patrec.2016.04.002
WOS KeywordPERSISTENT HOMOLOGY ; GAIT RECOGNITION ; CLASSIFICATION
Indexed BySCI ; ISTP
Language英语
Funding OrganizationNational Basic Research Program of China(2012C6316300) ; National Natural Science Foundation of China(61135002) ; State Key Laboratory of Mathematical Engineering and Advanced Computing(2015A06)
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000395616700022
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14428
Collection智能感知与计算研究中心
AffiliationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Ctr Res Intelligent Percept & Comp, 95 Zhongguancun East Rd, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Zhou, Zhen,Huang, Yongzhen,Wang, Liang,et al. Exploring generalized shape analysis by topological representations[J]. PATTERN RECOGNITION LETTERS,2017,87(87):177-185.
APA Zhou, Zhen,Huang, Yongzhen,Wang, Liang,&Tan, Tieniu.(2017).Exploring generalized shape analysis by topological representations.PATTERN RECOGNITION LETTERS,87(87),177-185.
MLA Zhou, Zhen,et al."Exploring generalized shape analysis by topological representations".PATTERN RECOGNITION LETTERS 87.87(2017):177-185.
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