Local Shape Descriptors, a Survey and Evaluation

Heider, Paul; Pierre-Pierre, Alain; Li, Ruosi; Grimm, Cindy

Local Shape Descriptors, a Survey and Evaluation

Files

049-056.pdf (570.02 KB)

AdditionalImages_workshop.pdf (20.32 MB)

Date

2011

Authors

Heider, Paul
Pierre-Pierre, Alain
Li, Ruosi
Grimm, Cindy

Publisher

The Eurographics Association

Abstract

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.

        @inproceedings{:10.2312/3DOR/3DOR11/049-056
,
booktitle = {Eurographics Workshop on 3D Object Retrieval
},
editor = {H. Laga and T. Schreck and A. Ferreira and A. Godil and I. Pratikakis and R. Veltkamp
},
title = {{Local Shape Descriptors, a Survey and Evaluation
}},
author = {Heider, Paul and 
Pierre-Pierre, Alain and 
Li, Ruosi and 
Grimm, Cindy
},
year = {2011
},
publisher = {The Eurographics Association
},
ISSN = {1997-0463
},
ISBN = {978-3-905674-31-6
},
DOI = {/10.2312/3DOR/3DOR11/049-056
}
}