Pose estimation of human face using synthesized model images

This paper presents a new method for pose estimation of the human face. The virtue of the method is the use a very simple calculation; correlation among multiple model images. It does not use any facial features such as organs or face gestalts. It is an improvement of the conventional template matching method, but to cope with deformation of facial pattern caused by its rotation or translation, some temporary model images are synthesized by using the generic S-dimensional shape model of the human face. A region of a face with various view directions is detected and then accumulated as a model image. It is arranged in “pose space”, according to its estimated view direction, and the pose of the face is estimated by a simple calculation of the correlation between multiple model images accumulated by that time. An experimental result using real moving images of various human faces is shown