Dense non-rigid surface registration using high-order graph matching

Abstract : In this paper, we propose a high-order graph matching formulation to address non-rigid surface matching. The singleton terms capture the geometric and appearance similarities (e.g., curvature and texture) while the high-order terms model the intrinsic embedding energy. The novelty of this paper includes: 1. casting 3D surface registration into a graph matching problem that combines both geometric and appearance similarities and intrinsic embedding information, 2. the first implementation of high-order graph matching algorithm that solves a non-convex optimization problem, and 3. an efficient two-stage optimization approach to constrain the search space for dense surface registration. Our method is validated through a series of experiments demonstrating its accuracy and efficiency, notably in challenging cases of large and/or non-isometric deformations, or meshes that are partially occluded.
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Communication dans un congrès
23rd IEEE Conference on Computer Vision and Pattern Recognition - CVPR 2010, Jun 2010, San Francisco, United States. pp.382-389, 2010, 〈10.1109/CVPR.2010.5540189〉
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Contributeur : Vivien Fécamp <>
Soumis le : vendredi 30 août 2013 - 14:01:47
Dernière modification le : mardi 5 février 2019 - 13:52:14

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Yun Zeng, Chaohui Wang, Yang Wang, Xianfeng Gu, Dimitris Samaras, et al.. Dense non-rigid surface registration using high-order graph matching. 23rd IEEE Conference on Computer Vision and Pattern Recognition - CVPR 2010, Jun 2010, San Francisco, United States. pp.382-389, 2010, 〈10.1109/CVPR.2010.5540189〉. 〈hal-00856064〉

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