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    SHREC '11: Robust Feature Detection and Description Benchmark

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    Date
    2011
    Author
    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.
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    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'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
    BibTeX
    @inproceedings {10.2312:3DOR:3DOR11:071-078,
    booktitle = {Eurographics Workshop on 3D Object Retrieval},
    editor = {H. Laga and T. Schreck and A. Ferreira and A. Godil and I. Pratikakis and R. Veltkamp},
    title = {{SHREC '11: Robust Feature Detection and Description Benchmark}},
    author = {Boyer, E. and Bronstein, A. M. and Bronstein, M. M. and Bustos, B. and Darom, T. and Horaud, R. and Hotz, I. and Keller, Y. and Keustermans, J. and Kovnatsky, A. and Litmany, R. and Reininghaus, J. and Sipiran, I. and Smeets, D. and Suetens, P. and Vandermeulen, D. and Zaharescu, A. and Zobel, V.},
    year = {2011},
    publisher = {The Eurographics Association},
    ISSN = {1997-0463},
    ISBN = {978-3-905674-31-6},
    DOI = {10.2312/3DOR/3DOR11/071-078}
    }
    URI
    http://dx.doi.org/10.2312/3DOR/3DOR11/071-078
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    • 3DOR 11

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    Eurographics Association copyright © 2013 - 2023 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA