MAP estimation of chin and cheek contours in video sequences
EURASIP Journal on Applied Signal Processing
Locating nose-tips and estimating head poses in images by tensorposes
IEEE Transactions on Circuits and Systems for Video Technology
Face localization via hierarchical CONDENSATION with fisher boosting feature selection
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
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For model-based coding of videophone sequences at very low bit rates, an algorithm for the automatic adaptation of a generic 3-D face model to individual faces in videophone sequences is presented. The face model is adapted to the individual facial features of the person-namely, to the eye centers, the eye corners, the eyelids, the irises, the mouth center, the mouth corners, the lips, the eyebrows, the nose, and the chin and cheek contours. First, these facial features are estimated from the videophone sequence. Then, using these estimated facial features, the 3-D face model is adapted to the individual face. Applying the presented algorithm to the videophone sequences Akiyo, Claire, and Miss America, all required facial features are successfully estimated, and face models are adapted. The distance between manually determined facial feature points in the image and projections of the corresponding vertices of the adapted 3-D face model onto the image plane is between 1.5 and 3.5 pels