Per-patch descriptor selection using surface and scene properties

Authors:
Ivo Everts;Jan C. van Gemert;Theo Gevers
Affiliations:
Intelligent Systems Lab Amsterdam (ISLA), University of Amsterdam, Amsterdam, The Netherlands;Intelligent Systems Lab Amsterdam (ISLA), University of Amsterdam, Amsterdam, The Netherlands;Intelligent Systems Lab Amsterdam (ISLA), University of Amsterdam, Amsterdam, The Netherlands
Venue:
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
Year:
2012

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Abstract

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.