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An Efficient Approach to Correspondences between Multiple Non‐Rigid Parts
Author(s) -
Tam Gary K.L.,
Martin Ralph R.,
Rosin Paul L.,
Lai YuKun
Publication year - 2014
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/cgf.12439
Subject(s) - computer science , polygon mesh , computer graphics , point (geometry) , rigid transformation , skinning , transformation (genetics) , process (computing) , computer vision , artificial intelligence , geometry processing , simple (philosophy) , displacement mapping , texture mapping , algorithm , computer graphics (images) , topology (electrical circuits) , mathematics , geometry , ecology , biochemistry , chemistry , philosophy , epistemology , combinatorics , gene , biology , operating system
Identifying multiple deformable parts on meshes and establishing dense correspondences between them are tasks of fundamental importance to computer graphics, with applications to e.g. geometric edit propagation and texture transfer. Much research has considered establishing correspondences between non‐rigid surfaces, but little work can both identify similar multiple deformable parts and handle partial shape correspondences. This paper addresses two related problems, treating them as a whole: (i) identifying similar deformable parts on a mesh, related by a non‐rigid transformation to a given query part, and (ii) establishing dense point correspondences automatically between such parts. We show that simple and efficient techniques can be developed if we make the assumption that these parts locally undergo isometric deformation. Our insight is that similar deformable parts are suggested by large clusters of point correspondences that are isometrically consistent. Once such parts are identified, dense point correspondences can be obtained by an iterative propagation process. Our techniques are applicable to models with arbitrary topology. Various examples demonstrate the effectiveness of our techniques.