TY - JOUR
T1 - Deformation-driven shape correspondence
AU - Zhang, H.
AU - Sheffer, A.
AU - Cohen-Or, D.
AU - Zhou, Q.
AU - van Kaick, O.
AU - Tagliasacchi, A.
N1 - Funding Information:
We are grateful to the Core Histology Unit and Imaging Group facilities for their outstanding technical assistance. We also thank the Proteomics, Genomics and Bioinformatics Unit at the CIMA. This work was supported by ‘UTE project FIMA’ agreement, The Cancer Research Thematic Network of the Health Institute Carlos III (RTICC RD06/0020/0066), PI042282, SAF-2009–11280, SAF2012-40056, grants 67/2005 and 09/2009 from the Government of Navarra, and ‘La Caixa Foundation’ to FL. DL-R was supported by the FIMA and FPU. IA was funded by the Basque Government. JDLR was supported by FIS-ISCIII grant PI12/00624. SV is an investigator of the Ramon y Cajal Program (MICINN, RYC-2011-09042).
PY - 2008
Y1 - 2008
N2 - Non-rigid 3D shape correspondence is a fundamental and difficult problem. Most applications which require a correspondence rely on manually selected markers. Without user assistance, the performances of existing automatic correspondence methods depend strongly on a good initial shape alignment or shape prior, and they generally do not tolerate large shape variations. We present an automatic feature correspondence algorithm capable of handling large, non-rigid shape variations, as well as partial matching. This is made possible by leveraging the power of state-of-the-art mesh deformation techniques and relying on a combinatorial tree traversal for correspondence search. The search is deformation-driven, prioritized by a self-distortion energy measured on meshes deformed according to a given correspondence. We demonstrate the ability of our approach to naturally match shapes which differ in pose, local scale, part decomposition, and geometric detail through numerous examples.
AB - Non-rigid 3D shape correspondence is a fundamental and difficult problem. Most applications which require a correspondence rely on manually selected markers. Without user assistance, the performances of existing automatic correspondence methods depend strongly on a good initial shape alignment or shape prior, and they generally do not tolerate large shape variations. We present an automatic feature correspondence algorithm capable of handling large, non-rigid shape variations, as well as partial matching. This is made possible by leveraging the power of state-of-the-art mesh deformation techniques and relying on a combinatorial tree traversal for correspondence search. The search is deformation-driven, prioritized by a self-distortion energy measured on meshes deformed according to a given correspondence. We demonstrate the ability of our approach to naturally match shapes which differ in pose, local scale, part decomposition, and geometric detail through numerous examples.
UR - http://www.scopus.com/inward/record.url?scp=78751633725&partnerID=8YFLogxK
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AN - SCOPUS:78751633725
VL - 27
SP - 1431
EP - 1439
JO - Eurographics Symposium on Geometry Processing
JF - Eurographics Symposium on Geometry Processing
SN - 1727-8384
IS - 5
ER -