“Non-rigid shape correspondence and description using geodesic field estimate distribution” by New, Mukhopadhyay, Arabnia and Bhandarkar
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Title:
- Non-rigid shape correspondence and description using geodesic field estimate distribution
Presenter(s)/Author(s):
Abstract:
Non-rigid shape description and analysis is an unsolved problem in computer graphics. Shape analysis is a fast evolving research field due to the wide availability of 3D shape databases. Widely studied methods for this family of problems include the Gromov Hausdorff distance [1], Bag-of-Features [2] and diffusion geometry [3]. The limitations of the Euclidian distance measure in the context of isometric deformation have made geodesic distance a de-facto standard for describing a metric space for non-rigid shape analysis. In this work, we propose a novel geodesic field space-based approach to describe and analyze non-rigid shapes from a point correspondence perspective.
References:
1. Memoli F., Sapiro G.: A theoretical and computational framework for isometry invariant recognition of point cloud data. Found. Comput. Math. 5, 3 (2005), 313–347.
2. Ovsjanikov, M., Bronstein, A. M., Bronstein, M. M., and Guibas, L. J. 2009. Shape Google: a computer vision approach to invariant shape retrieval. In Proc. NORDIA.
3. Sun, J., Ovsjanikov, M., and Guibas, L. J. 2009. A concise and provably informative multi-scale signature based on heat diffusion. In Proc. SGP.
4. Bhattacharyya, A. (1943). “On a measure of divergence between two statistical populations defined by their probability distributions”. Bulletin of the Calcutta Mathematical Society 35: 99–109.
5. http://tosca.cs.technion.ac.il/book/shrec.html
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