Geometric Models with Co-occurrence Groups

2011/01/30 by Bruna, Joan, Mallat, Stéphane
#Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Information Theory (cs.IT)

paper · doi:10.48550/arxiv.1101.5766

Abstract

A geometric model of sparse signal representations is introduced for classes of signals. It is computed by optimizing co-occurrence groups with a maximum likelihood estimate calculated with a Bernoulli mixture model. Applications to face image compression and MNIST digit classification illustrate the applicability of this model.

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