Face Detection by Integration of Evidence

M. Seshadrinathan and J. Ben-Arie (USA)

Keywords

Face detection, Skin color, YCbCr Color Space, RPROP neural network, Gabors, Ellipse Area Criterion, KL Trans form

Abstract

In this paper, we present a novel method for pose invariant face detection in color images. The novelty in our method arises from the integration of evidence from various inde pendent sources such as color, frequency response and ge ometric shape information. Skin color is detected in the Y-Cb-Cr color space using a RPROP neural network. The shape information is derived from a novel ellipse area cri terion and then it is formulated to compute a probabilistic score of the connected components that represent the faces in the images. The third source is based on Gabor 2D fil ters that are used to obtain frequency signature of faces in the images. The final likelihood of a face is a combination of the individual probabilities of color, shape and Gabor response.

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