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SHREC 2011: Robust Feature Detection and Description Benchmark

Boyer, E (author)
Grenoble, France
Bronstein, A.M. (author)
Tel Aviv University, Israel
Bronstein, M.M. (author)
Università della Svizzera Italiana, Lugano, Switzerland
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Bustos, B (author)
University of Chile
Darom, T (author)
Bar-Ilan University, Ramat-Gan, Israel
Horaud, R (author)
Grenoble, France
Hotz, Ingrid (author)
Zuse Institue Berlin
Kelle, Y (author)
Bar-Ilan University, Ramat-Gan, Israel
Keustermans, J (author)
K.U. Leuven, Belgium
Kovnatsky, A (author)
Israel Institute of Technology, Haifa, Israel
Litman, R (author)
Tel Aviv University, Israel
Reininghaus, Jan (author)
Zuse Institue Berlin
Sipiran, I (author)
University of Chile
Smeets, D (author)
K.U. Leuven, Belgium
Suetens, P (author)
K.U. Leuven, Belgium
Vandermeulen, D (author)
K.U. Leuven, Belgium
Zaharescu, A (author)
Waterloo, Canada
Zobel, Valentin (author)
Zuse Institut Berlin, Germany
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 (creator_code:org_t)
2011
2011
English.
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • 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.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)

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