A Multi-view Nonlinear Active Shape Model Based on 3D Transformation Shape Search

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.