SHREC '11: Robust Feature Detection and Description Benchmark [article]

E. Boyer, A. M. Bronstein, M. M. Bronstein, B. Bustos, T. Darom, R. Horaud, I. Hotz, Y. Keller, J. Keustermans, A. Kovnatsky, R. Litmany, J. Reininghaus (+6 others)
2011 Eurographics Workshop on 3D Object Retrieval, EG 3DOR  
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
more » ... g 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
doi:10.2312/3dor/3dor11/071-078 fatcat:qpw4lb4lafdstmor7nfo2ozp3a