Finding Human Faces with a Gaussian Mixture Distribution-Based Face Model

We present a distribution-based modeling scheme for representing and detecting human faces in cluttered scenes. A 2-Value metric is proposed for computing distance features between test patterns and the distribution-based model during classification. We present performance statistics of our overall system, and empirical results comparing the discriminative power of feature sets based on our 2-Value metric, versus similar feature sets based on other classical distribution dependent distance measures.

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