Face feature points extraction based on refined AAM
Masahide Kaneko · Applied science and technology · 2011
In this paper,we propose a robust facial feature points extraction method-LBP-AAM(L-AAM),using active appearance model(AAM) based on local binary pattern(LBP) texture features.We firstly generated three types of model instances(frontal,left-rotated and right-rotated),and LBP was used to judge the type of test facial image and predict the rotation of the test the face,and according to the prediction we selected proper model instances as the fitting model.Finally we extracted the feature points of the face.Experimental results proved that this method increased the fitting accuracy rate by about 27% and the time consumption was decreased by about 9% comparing with the standard AAM method.