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Facial action detection from dual-view static face images

Maja Pantic, Leon Rothkrantz

Conference or Workshop Paper
IEEE Int'l Conf. on Fuzzy Systems 2004
July, 2004
Volume 1
ISBN 0-7803-8360-5

This paper presents an automatic system that we developed for automatic recognition of facial gestures (facial muscle activity) from static images of combined frontal- and profile-view of the face. For the frontal view, the face region is subjected to multi-detector processing which per facial component (eyes, eyebrows, mouth), generates a spatial sample of its contour. A set of 19 frontal-face feature points is then extracted from the spatially sampled contours of the facial features. For the profile view, 10 feature points are extracted from the contour of the face-profile region. Based on these 29 points, 29 individual facial muscle action units (AUs) occurring alone or in combinations in an input dual-view image are recognized using a rule-based reasoning. With each scored AU, the utilized algorithm associates a factor denoting the certainty with which the pertinent AU has been scored. A recognition rate of 86% is achieved.

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