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A spectral representation for appearance-based classification and recognition | IEEE Conference Publication | IEEE Xplore

A spectral representation for appearance-based classification and recognition


Abstract:

We present a spectral representation for appearance based image classification and object recognition. Based on a generative process, the representation is derived by par...Show More

Abstract:

We present a spectral representation for appearance based image classification and object recognition. Based on a generative process, the representation is derived by partitioning the frequency domain into small disjoint regions. This gives rise to a set of filters and a representation consisting of marginal distributions of those filter responses. We use a neural network, to learn a classifier through training examples. We propose a filter selection algorithm by maximizing the performance over training data. A distinct advantage of our representation is that it can be effectively used for different classification and recognition tasks, which is demonstrated by experiments and comparisons in texture classification, face recognition, and appearance-based 3D object recognition.
Date of Conference: 11-15 August 2002
Date Added to IEEE Xplore: 10 December 2002
Print ISBN:0-7695-1695-X
Print ISSN: 1051-4651
Conference Location: Quebec City, QC, Canada

References

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