DocumentCode
794419
Title
Curvature-based algorithms for nonrigid motion and correspondence estimation
Author
Laskov, Pavel ; Kambhamettu, Chandra
Author_Institution
Fraunhofer Inst. FIRST, Berlin, Germany
Volume
25
Issue
10
fYear
2003
Firstpage
1349
Lastpage
1354
Abstract
We present a novel technique for utilizing the Gaussian curvature information in 3D nonrigid motion estimation in the absence of known correspondence. Differential-geometric constraints derived in the paper allow one to estimate parameters of the local affine motion model given the values of Gaussian curvature before and after motion. These constraints can be further combined with the previously known constraints based on the unit normals before and after motion. Our experiments demonstrate that the resulting hybrid algorithm is more accurate than each of its constituents and more accurate than the classical ICP algorithm. We also present a technique for curvilinear orthogonalization of quadratic Monge patches that is essential in our derivation and useful in other applications.
Keywords
computational geometry; differential geometry; motion estimation; parameter estimation; 3D nonrigid motion estimation; Gaussian curvature; Gaussian curvature information; correspondence estimation; curvature-based algorithms; curvilinear orthogonalization; differential geometry; differential-geometric constraints; hybrid algorithm; local affine motion model; parameter estimation; quadratic Monge patches; unit normals; Application software; Biomedical imaging; Computational geometry; Computer vision; Iterative closest point algorithm; Layout; Motion analysis; Motion estimation; Parameter estimation; Solid modeling;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/TPAMI.2003.1233911
Filename
1233911
Link To Document