A Multi-view Nonlinear Active Shape Model Based on 3D Transformation Shape Search
Faling Yi, Wei Xiong, Huang Zhanpeng, Zhao Jie · 2009
Active shape model (ASM) is an efficient method for locating face feature points. When the face poses vary largely, it is difficult for the two-dimension (2D) transformation shape search method in previous works to cope with this kind of nonlinear shape variations. We propose a novel shape search method of the three-dimension (3D) transformation; and the variation of the face pose can simulated by 3D transformation shape search correctly. The method includes the following steps: firstly, constructing an average face 3D model; secondly, by the average face 3D model, making 2D initial shape get the third dimension coordinate in the face images of ASM training set; thirdly, tracking the object shape by 3D transforming and projecting to 2D view-plane based on the 3D initial shape. In the third step, 3D transformation shape search is implemented by the two-step transformation. The 10 pose parameters of 3D transformation are calculated after the two step transformations are iterated into the pre-defining precision. The test data shows the 3D transformation shape search method has better performance than the current standard 2D transformation while the face poses vary largely.