Face recognition based on LBPH and regression of Local Binary features

This paper presents a system to recognize face by a variation of LBPH. We use a method of regression of local binary features to get the landmark of face image whose computational complexity is very low. We utilize these landmark points which can be trained to align the face, to extract the facial features. By calculating the Local Binary Patterns Histogram (LBPH) of these landmark points and its neighborhood pixels, we can extract effective facial feature to realize face recognition. This method can increase the calculating speed of LBPH and also can improve the recognition rate. Finally, we show the experimental results using this method to recognize face.