SHREC '11: Robust Feature Detection and Description Benchmark

Abstract
Feature-based approaches have recently become very popular in computer vision and image analysis applications, and are becoming a promising direction in shape retrieval. SHREC'11 robust feature detection and description benchmark simulates the feature detection and description stages of feature-based shape retrieval algorithms. The benchmark tests the performance of shape feature detectors and descriptors under a wide variety of transformations. The benchmark allows evaluating how algorithms cope with certain classes of transformations and strength of the transformations that can be dealt with. The present paper is a report of the SHREC'11 robust feature detection and description benchmark results
Description

        
@inproceedings{
:10.2312/3DOR/3DOR11/071-078
, 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 = {{
SHREC '11: Robust Feature Detection and Description Benchmark
}}, author = {
Boyer, E.
and
Bronstein, A. M.
and
Litmany, R.
and
Reininghaus, J.
and
Sipiran, I.
and
Smeets, D.
and
Suetens, P.
and
Vandermeulen, D.
and
Zaharescu, A.
and
Zobel, V.
and
Bronstein, M. M.
and
Bustos, B.
and
Darom, T.
and
Horaud, R.
and
Hotz, I.
and
Keller, Y.
and
Keustermans, J.
and
Kovnatsky, A.
}, year = {
2011
}, publisher = {
The Eurographics Association
}, ISSN = {
1997-0463
}, ISBN = {
978-3-905674-31-6
}, DOI = {
/10.2312/3DOR/3DOR11/071-078
} }
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