Growing Least Squares for the Analysis of Manifolds in Scale-Space

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dc.contributor.authorMellado, Nicolasen_US
dc.contributor.authorGuennebaud, Gaƫlen_US
dc.contributor.authorBarla, Pascalen_US
dc.contributor.authorReuter, Patricken_US
dc.contributor.authorSchlick, Christopheen_US
dc.contributor.editorEitan Grinspun and Niloy Mitraen_US
dc.date.accessioned2015-02-28T07:44:11Z
dc.date.available2015-02-28T07:44:11Z
dc.date.issued2012en_US
dc.description.abstractWe 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.en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume31
dc.identifier.doi10.1111/j.1467-8659.2012.03174.x
dc.identifier.issn1467-8659en_US
dc.identifier.urihttps://doi.org/10.1111/j.1467-8659.2012.03174.xen_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.titleGrowing Least Squares for the Analysis of Manifolds in Scale-Spaceen_US
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SGP12: Eurographics Symposium on Geometry Processing