Computer Science – Computer Vision and Pattern Recognition
Scientific paper
2011-02-21
Computer Science
Computer Vision and Pattern Recognition
This is a full version of the SHREC'11 report published in 3DOR
Scientific paper
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.
Boyer E.
Bronstein Alexander M.
Bronstein Michael M.
Bustos B.
Darom T.
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