PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Material-Specific Adaptation of Color Invariant Features
Gertjan J. Burghouts and Jan-Mark Geusebroek
Pattern Recognition Letters Volume 30, pp. 306-313, 2009.


For the modeling of materials, the mapping of image features onto a codebook of feature representatives receives extensive treatment. For reason of their generality and simplicity, filterbank outputs are commonly used as features. The MR8 filterbank of Varma and Zisserman is performing well in a recent evaluation. In this paper, we construct color invariant filter sets from the original MR8 filterbank. We evaluate several color invariant alternatives over more than 250 real-world materials recorded under a variety of imaging conditions including clutter. Our contribution is a material recognition framework that learns automatically for each material specifically the most discriminative filterbank combination and corresponding degree of color invariance. For a large set of materials each with different physical properties, we demonstrate the material-specific filterbank models to be preferred over models with fixed filterbanks.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:6154
Deposited By:Christof Monz
Deposited On:08 March 2010