Mesh analysis using geodesic mean-shift

Lior Shapira, Ariel Shamir, and Daniel Cohen-Or

Abstract

In this paper we introduce a versatile and robust method for analyzing the feature space associated with a given mesh surface. The method is based on the mean-shift operator which was shown to be successful in image and video processing. Its strength lays in the fact that it works in a single joint space of geometry and attributes called the feature-space. The mean-shift procedure works as a gradient ascend finding maxima of an estimated probability density function in feature-space. Our method for using the meanshift technique on surfaces solves several difficulties. First, meshes as opposed to images do not present a regular and uniform sampling of domain. Second, on surfaces meshes the shifting procedure must be constrained to stay on the surface and preserve geodesic distances. We define a special local geodesic parameterizations scheme, and use it to generalize the mean-shift procedure to unstructured surface meshes. Our method can support piecewise linear attribute definitions as well as piecewise constant attributes.

Details

Publication typeArticle
Published inVisual Computer
URLhttp://dx.doi.org/10.1007/s00371-006-0370-2
Pages99–108
Volume22
Number2
AddressSecaucus, NJ, USA
PublisherSpringer-Verlag New York, Inc.
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