Local Shape Descriptors, A Survey and Evaluation
Published in Proceedings of the 4th Eurographics Conference on 3D Object Retrieval, 2011
Sourcecode available at <a ref=\"http://sourceforge.net/projects/meshprocessing/\">Sourceforge</a>, Local shape descriptors can be used for a variety of tasks, from registration to comparison to shape analysis and retrieval. There have been a variety of local shape descriptors developed for these tasks, which have been evaluated in isolation or in pairs, but not against each other. We provide a survey of existing descriptors and a framework for comparing them. We perform a detailed evaluation of the descriptors using real data sets from a variety of sources. We first evaluate how stable these metrics are under changes in mesh resolution, noise, and smoothing. We then analyze the discriminatory ability of the descriptors for the task of shape matching. Our conclusion is that sampling the normal distribution and the mean curvature, using 25 samples, and reducing this data to 5-10 samples via Principal Components Analysis provides robustness to noise and the best shape discrimination results. Local shape descriptors, spin images, heat map, curvature, shape matching, feature matching
authors: Paul Heider and Alain Pierre-Pierre and Ruosi Li and Cindy Grimm
Authors: Paul Heider and Alain Pierre-Pierre and Ruosi Li and Cindy Grimm
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