Lasso based shape regression for face alignment

Face alignment focuses on the problem for localizing facial landmarks and it is an important topic of face recognition, beautification and facial expression analysis etc. Based on Explicit Shape Regression (ESR) framework, we proposed a face alignment algorithm using Lasso regression by adding a L₁ norm constraint on the model parameters to reduce the size of shape model while maintaining the resultant performance. Meanwhile, a face ratio transformation method is proposed by using the face ratio to adjust the estimation result of face landmarks. The method can be used to solve the problem of mutual influence among various training samples in different scales. Experimental results show that the overall system performs well in related dataset and it can run in real-time and be insensitive to human faces in multiple poses.