Abstract

Current face identification systems are not robust enough to accurately identify the same individual in different images with changes in head pose, facial expression, occlusion, length of hair, illumination, aging, etc. This is especially a problem for facial images that are captured using low resolution video cameras or webcams. This paper introduces a new technique for facial identification in low resolution images that combines facial structure with skin texture to accommodate changes in lighting and head pose. Experiments using this new technique show that combining facial structure features with skin texture features results in a facial identification system for low resolution images that is more robust to pose and illumination conditions than either technique used alone.

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