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The paper presents an extension of active appearance models (AAMs) that is better capable of dealing with the large variation in face appearance that is encountered in large multi-person face data sets. Instead of the traditional PCA-based texture model, our extended AAM employs a mixture of probabilistic PCA to describe texture variation, leading to a richer model. The resulting extended AAM can...
Automatically locating multiple feature points (i.e., the shape) in a facial image and then synthesizing the corresponding facial sketch are highly challenging since facial images typically exhibit a wide range of poses, expressions, and scales, and have differing degrees of illumination and/or occlusion. When the facial sketches are to be synthesized in the unique sketching style of a particular...
Statistical methods of shape and appearance are powerful tools used in computer vision for near-correct interpretation of images. In this paper, we present a method for classifying facial expressions based on the extracted features of facial components. The face, the window to the inner self of an individual can be analyzed for outright expressions like sadness, happiness, anger, surprise, disgust...
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