Mesh analysis using geodesic mean-shift

Lior Shapira, Ariel Shamir, and Daniel Cohen-Or


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.


Publication typeArticle
Published inVisual Computer
AddressSecaucus, NJ, USA
PublisherSpringer-Verlag New York, Inc.
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