Abstract
This paper describes a synthesis-by-analysis approach using cylindrical range images for producing human facial images with realistic expressions. First view-independent representations of 3D locations of facial feature points are obtained by using an object-centered coordinate system defined on a face. Then we quantify facial feature points locations for the neutral expression, and six primary expressions: anger, disgust, surprise, fear, happiness and sadness Applying an image warping technique to both range and texture images, we finally generate 3D facial expression images from neutral expression images using motion vectors of facial feature points.
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