Face pose estimating system based on eigenspace analysis

In this paper, we propose a new system for estimating face pose from a facial image. In this system, an input facial image is compared with a database of images of various face pose, then the matched image provides the face pose. The database of images includes not only various face poses but also various illumination conditions, so that the face pose estimation system can be used under various illumination conditions. For collecting such various facial images, they are generated by computer, rather than using real images. The eigenspace method is used for searching a matched image with an input facial image. Since various illumination images are collected in the database of facial images, the extracted principle eigenvectors mostly depend on the face pose. By performing the matching process in the eigenspace, a matched image with the input facial image can be found. The pose of the matched image is closest to the input face. The matching process is also fast because it is performed in small dimensional space spanned by selected eigenvectors only. The proposed pose estimation system can continuously track the face pose of different persons under different light conditions