Face Alignment Based on Weighted Active Shape Models
基于加权主动形状建模的人脸特征定位方法

Active Shape Models (ASM) is one of powerful tools for face alignment and face recognition. However, the performance of ASM is often influenced by some factors such as the initial location, illumination and so on, which will frequently lead to the local minima in optimization. This paper proposes a weighted Active Shape Models, in which the more robust local appearance model is constructed with the local information of each landmark fully. Through the improved method the local minima problem can be solved efficiently, extracted the detailed local information of face feature points and localized the points accurately. Experiments verify the above conclusions.