Name
Abstract | ||
|---|---|---|
We construct a scale space of shape of closed Riemannian manifolds, equipped with metrics derived from spectral representations and the Hausdorff distance. The representation depends only on the intrinsic geometry of the manifolds, making it robust to pose and articulation. The computation of shape distance involves an optimization problem over the 2^p-element group of all p-bit strings, which is approached with Markov chain Monte Carlo techniques. The methods are applied to cluster surfaces in 3D space. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICPR.2010.649 | Pattern Recognition |
Keywords | Field | DocType |
scale-space spectral representation,intrinsic geometry,hausdorff distance,p-bit string,closed riemannian manifold,shape distance,cluster surface,optimization problem,monte carlo technique,markov chain,scale space,computational geometry,manifolds,heating,kernel,markov chain monte carlo,measurement,heat kernel,markov processes,shape | Topology,Markov process,Markov chain Monte Carlo,Computer science,Computational geometry,Markov chain,Scale space,Hausdorff distance,Riemannian geometry,Manifold | Conference |
ISSN | ISBN | Citations |
1051-4651 | 978-1-4244-7542-1 | 2 |
PageRank | References | Authors |
0.42 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jonathan Bates | 1 | 17 | 2.49 |
| Xiuwen Liu | 2 | 744 | 80.44 |
| Washington Mio | 3 | 544 | 40.82 |