SHREC 2011: 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.
Cite
@article{arxiv.1102.4258,
title = {SHREC 2011: robust feature detection and description benchmark},
author = {E. Boyer and A. M. Bronstein and M. M. Bronstein and B. Bustos and T. Darom and R. Horaud and I. Hotz and Y. Keller and J. Keustermans and A. Kovnatsky and R. Litman and J. Reininghaus and I. Sipiran and D. Smeets and P. Suetens and D. Vandermeulen and A. Zaharescu and V. Zobel},
journal= {arXiv preprint arXiv:1102.4258},
year = {2011}
}
Comments
This is a full version of the SHREC'11 report published in 3DOR