- Per-patch descriptor selection using surface and scene properties
- Lecture Notes in Computer Science
- Pages (from-to)
- Document type
- Faculty of Science (FNWI)
- Informatics Institute (IVI)
Local image descriptors are generally designed for describing all possible image patches. Such patches may be subject to complex variations in appearance due to incidental object, scene and recording conditions. Because of this, a single-best descriptor for accurate image representation under all conditions does not exist. Therefore, we propose to automatically select from a pool of descriptors the one that is best suitable based on object surface and scene properties. These properties are measured on the fly from a single image patch through a set of attributes. Attributes are input to a classifier which selects the best descriptor. Our experiments on a large dataset of colored object patches show that the proposed selection method outperforms the best single descriptor and a-priori combinations of the descriptor pool.
- go to publisher's site
- Proceedings title: Computer vision - ECCV 2012: 12th European conference on computer vision, Florence, Italy, October 7-13,
2012, proceedings, part VI
Place of publication: Berlin
Editors: A. Fitzgibbon, S. Lazebnik, P. Perona, Y. Sato, C. Schmid
If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library, or send a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible.