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

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Date
2012
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association and Blackwell Publishing Ltd.
Abstract
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.
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@article{
10.1111:j.1467-8659.2012.03174.x
, journal = {Computer Graphics Forum}, title = {{
Growing Least Squares for the Analysis of Manifolds in Scale-Space
}}, author = {
Mellado, Nicolas
and
Guennebaud, Gaƫl
and
Barla, Pascal
and
Reuter, Patrick
and
Schlick, Christophe
}, year = {
2012
}, publisher = {
The Eurographics Association and Blackwell Publishing Ltd.
}, ISSN = {
1467-8659
}, DOI = {
10.1111/j.1467-8659.2012.03174.x
} }
Citation