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We propose a novel efficient 3-dimensional geomet- rical consistency criterion for detection of a set of fa- cial feature points. Many face recognition methods em- ploying a single image require localization of particular facial feature points and their performance is highly de- pendent on localization accuracy in detecting these fea- ture points. The proposed method is able to calculate alignment error of a point set rapidly because calcula- tion is not iterative. Also the method does not depend on the type of point detection method used and no learn- ing is needed. Independently detected point sets are evaluated through matching to a 3-dimensional generic face model. Correspondence error is defined by the dis- tance between the feature points defined in the model and those detected. The proposed criterion is evaluated through experiment using various facial feature point sets on face images.

An Efficient 3D Geometrical Consistency Criterion for Detection of a Set of Facial Feature Points