Robust real-time face alignment based on ASM with boosting regression for displacement prediction

Face alignment is a critical problem in many face related applications such as facial expression analysis, face recognition, etc. This paper presents a novel real time face alignment algorithm based on active shape model (ASM). In our algorithm, local textures of each label point is used to predict the displacement of each label point by applying boost non-linear regressions on the local search stage of the ASM framework. Experiments on different datasets show that our algorithm is much faster in speed and more robust to the initialization than previous ASM method.