Human faces differ in shape and texture. Image representations based on this separation of shape and texture information have been reported by several authors [for a review, see Science 272, 1905 (1996)]. We investigate such a representation of human faces based on a separation of texture and two-dimensional shape information. Texture and shape were separated by use of pixel-by-pixel correspondence among the various images, which was established through algorithms known from optical flow computation. We demonstrate the improvement of the proposed representation over well-established pixel-based techniques in terms of coding efficiency and in terms of the ability to generalize to new images of faces. The evaluation is performed by calculating different distance measures between the original image and its reconstruction and by measuring the time that human subjects need to discriminate them.
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