2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'04) - Volume 2 Diffeomorphic Matching of Distributions: A New Approach for Unlabelled Point-Sets and Sub-Manifolds Matching Washington, D.C., USA June 27-July 02 ISBN: 0-7695-2158-4
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CVPR.2004.81
In the paper, we study the problem of optimal matching of two generalized functions (distributions) via a diffeomorphic transformation of the ambient space. In the particular case of discrete distributions (weighted sums of Dirac measures), we provide a new algorithm to compare two arbitrary unlabelled sets of points, and show that it behaves properly in limit of continuous distributions on submanifolds. As a consequence, the algorithm may apply to various matching problems, such as curve or surface matching (via a sub-sampling), or mixings of landmark and curve data. As the solution forbids high energy solutions, it is also robust towards addition of noise and the technique can be used for nonlinear projection of datasets. We present 2D and 3D experiments.
Citation:
Joan Glaunes, Alain Trouvé, Laurent Younes, "Diffeomorphic Matching of Distributions: A New Approach for Unlabelled Point-Sets and Sub-Manifolds Matching," cvpr, vol. 2, pp.712-718, 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'04) - Volume 2, 2004 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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