hal-00713678, version 1
Growing Least Squares for the Continuous Analysis of Manifolds in Scale-Space
1, 2 1, 2 1, 2, 3 a, 1, 2, 3 a, 1, 2
Computer Graphics Forum (2012)
Résumé : We present a novel approach to the multi-scale analysis of point-sampled manifolds of co-dimension 1. It is based on a variant of Moving Least Squares, whereby the evolution of a geometric descriptor at increasing scales is used to locate pertinent locations in scale-space, hence the name "Growing Least Squares". Compared to existing scale-space analysis methods, our approach is the first to provide a continuous solution in space and scale dimensions, without requiring any parametrization, connectivity or uniform sampling. An important implication is that we identify multiple pertinent scales for any point on a manifold, a property that had not yet been demonstrated in the literature. In practice, our approach exhibits an improved robustness to change of input, and is easily implemented in a parallel fashion on the GPU. We compare our method to state-of-the-art scale-space analysis techniques and illustrate its practical relevance in a few application scenarios.
- a – Université de Bordeaux 2
- 1 :
- CNRS : UMR5800 – Université Sciences et Technologies - Bordeaux I – École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB) – Université Victor Segalen - Bordeaux II
- 2 :
- INRIA
- 3 :
- Institut d'Optique Graduate School (IOGS) – CNRS : UMR5298 – Université Sciences et Technologies - Bordeaux I
- Domaine : Informatique/Géométrie algorithmique
- hal-00713678, version 1
- http://hal.inria.fr/hal-00713678
- oai:hal.inria.fr:hal-00713678
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- Soumis le : Mercredi 18 Juillet 2012, 23:49:22
- Dernière modification le : Mardi 21 Août 2012, 14:13:22
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