We describe a novel shape constraint technique which is incorporated into a multi-stage algorithm to automatically locate features on the human face. The method is coarse-to-fine. First a face detector is applied to find the approximate scale and location of the face in the image. Then individual feature detectors are applied and combined using a novel algorithm known as Pairwise Reinforcement of Feature Responses (PRFR). The points predicted by this method are then refined using a version of the Active Appearance Model (AAM) search, which is tuned to edge and corner features. The final output of the three stage algorithm is shown to give much better results than any other combination of methods. The method outperforms previous published results on the BIOID test set [11] .
In REF a hybrid method is proposed to extract features of the human face.
A multi-stage approach to facial feature detection
In British Machine Vision Conference
Computer Science