Aiming at the problem that the existing robust cascade postural regression algorithm lacks shape constraint, and has low localization accuracy and unsatisfactory success rate in complex face and occlusion situations, a novel positioning algorithm for pose estimation of facial feature points was proposed to improve the accuracy and success rate. A regional block operation was performed on face feature points to implement shape constraint. To improve the algorithm performance, a regression operation was performed on partial feature point positions to reduce the scale of regression, and the shape index feature was introduced to sampling prior operation. The experimental results show that the proposed algorithm has higher localization accuracy and robustness for complex face and occlusion, and meets the realtime requirement.