Publication:
3D articulated shape segmentation using motion information

dc.contributor.departmentDepartment of Computer Engineering
dc.contributor.departmentN/A
dc.contributor.kuauthorYemez, Yücel
dc.contributor.kuauthorKalafatlar, Emre
dc.contributor.kuprofileFaculty Member
dc.contributor.kuprofileMaster Student
dc.contributor.otherDepartment of Computer Engineering
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.schoolcollegeinstituteGraduate School of Sciences and Engineering
dc.contributor.yokid107907
dc.contributor.yokidN/A
dc.date.accessioned2024-11-09T23:06:43Z
dc.date.issued2010
dc.description.abstractWe present a method for segmentation of articulated 3D shapes by incorporating the motion information obtained from time-varying models. We assume that the articulated shape is given in the form of a mesh sequence with fixed connectivity so that the inter-frame vertex correspondences, hence the vertex movements, are known a priori. We use different postures of an articulated shape in multiple frames to constitute an affinity matrix which encodes both temporal and spatial similarities between surface points. The shape is then decomposed into segments in spectral domain based on the affinity matrix using a standard K-means clustering algorithm. The performance of the proposed segmentation method is demonstrated on the mesh sequence of a human actor.
dc.description.indexedbyScopus
dc.description.openaccessYES
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuTÜBİTAK
dc.identifier.doi10.1109/ICPR.2010.877
dc.identifier.isbn9780-7695-4109-9
dc.identifier.issn1051-4651
dc.identifier.linkhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-78149480040anddoi=10.1109%2fICPR.2010.877andpartnerID=40andmd5=9d1cfedaa4408bb28aad3871ef13e7cb
dc.identifier.quartileN/A
dc.identifier.scopus2-s2.0-78149480040
dc.identifier.urihttp://dx.doi.org/10.1109/ICPR.2010.877
dc.identifier.urihttps://hdl.handle.net/20.500.14288/9023
dc.keywords3-D shape
dc.keywordsAffinity matrix
dc.keywordsHuman actor
dc.keywordsInter-frame
dc.keywordsK-Means clustering algorithm
dc.keywordsMotion information
dc.keywordsMultiple-frame
dc.keywordsSegmentation methods
dc.keywordsShape segmentation
dc.keywordsSpatial similarity
dc.keywordsSpectral domains
dc.keywordsSurface points
dc.keywordsTime-varying models
dc.keywordsVertex correspondence
dc.keywordsClustering algorithms
dc.keywordsPattern recognition
dc.keywordsThree dimensional
dc.languageEnglish
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.sourceProceedings - International Conference on Pattern Recognition
dc.subjectComputer engineering
dc.title3D articulated shape segmentation using motion information
dc.typeConference proceeding
dspace.entity.typePublication
local.contributor.authorid0000-0002-7515-3138
local.contributor.authoridN/A
local.contributor.kuauthorYemez, Yücel
local.contributor.kuauthorKalafatlar, Emre
relation.isOrgUnitOfPublication89352e43-bf09-4ef4-82f6-6f9d0174ebae
relation.isOrgUnitOfPublication.latestForDiscovery89352e43-bf09-4ef4-82f6-6f9d0174ebae

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