3DOR 11
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Browsing 3DOR 11 by Subject "Categories and Subject Descriptors (according to ACM CCS): H.3.2 [Information storage and retrieval]: Information Search and Retrieval-Retrieval models I.2.10 [Artificial intelligence]: Vision and Scene Understanding-Shape"
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Item SHREC '11: Robust Feature Detection and Description Benchmark(The Eurographics Association, 2011) Boyer, E.; Bronstein, A. M.; Bronstein, M. M.; Bustos, B.; Darom, T.; Horaud, R.; Hotz, I.; Keller, Y.; Keustermans, J.; Kovnatsky, A.; Litmany, R.; Reininghaus, J.; Sipiran, I.; Smeets, D.; Suetens, P.; Vandermeulen, D.; Zaharescu, A.; Zobel, V.; H. Laga and T. Schreck and A. Ferreira and A. Godil and I. Pratikakis and R. VeltkampFeature-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