Detection and pose estimation of human face with synthesized image models

This paper presents a new method for detecting a human face, and estimating its pose while tracking it in real image sequences. The virtue of the method is that parameterized qualitative features derived from a lot of sampled facial images are introduced in the detection process, and in the face tracking process, some temporary model images of the face with various poses are synthesized by a texture mapping technique and utilized. While tracking the detected face, many model images are accumulated and the pose of the human face is estimated as a linear combination of correlations between the models.