Publication:
Non-rigid 3D shape tracking from multiview video

dc.contributor.departmentDepartment of Computer Engineering
dc.contributor.departmentGraduate School of Sciences and Engineering
dc.contributor.kuauthorBilir, Salih Cihan
dc.contributor.kuauthorYemez, Yücel
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.schoolcollegeinstituteGRADUATE SCHOOL OF SCIENCES AND ENGINEERING
dc.date.accessioned2024-11-09T23:04:12Z
dc.date.issued2012
dc.description.abstractWe present a fast and efficient non-rigid shape tracking method for modeling dynamic 3D objects from multiview video. Starting from an initial mesh representation, the shape of a dynamic object is tracked over time, both in geometry and topology, based on multiview silhouette and 3D scene flow information. The mesh representation of each frame is obtained by deforming the mesh representation of the previous frame towards the optimal surface defined by the time-varying multiview silhouette information with the aid of 3D scene flow vectors. The whole time-varying shape is then represented as a mesh sequence which can efficiently be encoded in terms of restructuring and topological operations, and small-scale vertex displacements along with the initial model. The proposed method has the ability to deal with dynamic objects that may undergo non-rigid transformations and topological changes. The time-varying mesh representations of such non-rigid shapes, which are not necessarily of fixed connectivity, can successfully be tracked thanks to restructuring and topological operations employed in our deformation scheme. We demonstrate the performance of the proposed method both on real and synthetic sequences. (C) 2012 Elsevier Inc. All rights reserved.
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.issue11
dc.description.openaccessNO
dc.description.sponsoredbyTubitakEuN/A
dc.description.sponsorshipTUBITAK [EEEAG-105E143] This work has been supported by TUBITAK under the Project EEEAG-105E143.
dc.description.volume116
dc.identifier.doi10.1016/j.cviu.2012.07.001
dc.identifier.eissn1090-235X
dc.identifier.issn1077-3142
dc.identifier.scopus2-s2.0-84866634770
dc.identifier.urihttps://doi.org/10.1016/j.cviu.2012.07.001
dc.identifier.urihttps://hdl.handle.net/20.500.14288/8586
dc.identifier.wos309629600003
dc.keywords3D Shape tracking
dc.keywordsMesh deformation
dc.keywords3D scene flow
dc.keywordsShape from silhouette
dc.keywords3D Video
dc.keywordsMesh
dc.keywordsDeformation
dc.keywordsSilhouette
dc.keywordsCapture
dc.keywordsStereo
dc.language.isoeng
dc.publisherAcademic Press Inc Elsevier Science
dc.relation.ispartofComputer Vision And Image Understanding
dc.subjectComputer science
dc.subjectArtificial intelligence
dc.subjectEngineering
dc.subjectElectrical electronic engineering
dc.titleNon-rigid 3D shape tracking from multiview video
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.kuauthorBilir, Salih Cihan
local.contributor.kuauthorYemez, Yücel
local.publication.orgunit1GRADUATE SCHOOL OF SCIENCES AND ENGINEERING
local.publication.orgunit1College of Engineering
local.publication.orgunit2Department of Computer Engineering
local.publication.orgunit2Graduate School of Sciences and Engineering
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