In many face recognition tasks the pose of the probe and gallery images are different. In other cases multiple gallery or probe images may be available, each captured from a different pose. We have developed a face recognition algorithm that is able to handle large variations in pose using a “patch-based” rather than “holistic” representations. The algorithm operates by estimating the “eigen light-field” of the subject’s head from the input gallery or probe images. Matching between the probe and gallery is then performed using the eigen light-fields.

Our algorithm drammatically out-performs, FaceIT, a commercially available system from Visionics Corporations. A brief summary of our results on the PIE Database
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