SHREC'10 track: feature detection and description

Authors:
A. M. Bronstein;M. M. Bronstein;B. Bustos;U. Castellani;M. Crisani;B. Falcidieno;L. J. Guibas;I. Kokkinos;V. Murino;M. Ovsjanikov;G. Patané;I. Sipiran;M. Spagnuolo;J. Sun
Affiliations:
Department of Computer Science, Technion-Israel Institute of Technology;Department of Computer Science, Technion-Israel Institute of Technology;Department of Computer Science, University of Chile;Department of Computer Science, University of Verona;Department of Computer Science, University of Verona and Italian Institute of Technology, Genova;CNR-IMATI Genova;Department of Computer Science, Stanford University;Deparment of Applied Mathematics, École Centrale de Paris;Department of Computer Science, University of Verona and Italian Institute of Technology, Genova;Institute for Computational and Mathematical Engineering, Stanford University;CNR-IMATI Genova;Department of Computer Science, University of Chile;CNR-IMATI Genova;Princeton University
Venue:
EG 3DOR'10 Proceedings of the 3rd Eurographics conference on 3D Object Retrieval
Year:
2010

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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. The SHREC'10 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 3D Shape Retrieval Contest 2010 (SHREC'10) feature detection and description benchmark results.