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We introduce a framework for locating the facial features that are robust to varying conditions in lighting, scale, position and orientation. This facial feature extraction algorithm could be useful as a front-end for a face recognition system either to normalize the data or provide the critical features for the classification. We are currently developing a face recognition algorithm which will incorporate the facial feature location algorithm described here. The algorithm is based on a general template which outlines different regions of the face. The template is matched to a particular image location where a set of a priori constraints are best met. The constraints are chosen to be invariant over a wide set of facial characteristics and external conditions. The constraints include ratios of average intensity values, average chrominance values and average smoothness values. The idea of constructing a general template and a set of a priori constraints could easily be extended to other objects.
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Xiaoyu Zhang, Christine I. Podilchuk, "Face location and recognition," Proc. SPIE 2657, Human Vision and Electronic Imaging, (22 April 1996); https://doi.org/10.1117/12.238723