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’10 robust feature detection and descriptionbenchmark 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 andstrength of the transformations that can be dealt with. The present paper is a report of the SHREC’10 robustfeature detection and description benchmark results.
SHREC 2010: robust feature detection and description benchmark
CASTELLANI, Umberto;CRISTANI, Marco;MURINO, Vittorio;
2010-01-01
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’10 robust feature detection and descriptionbenchmark 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 andstrength of the transformations that can be dealt with. The present paper is a report of the SHREC’10 robustfeature detection and description benchmark results.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.