Face pose estimation with a knowledge-based model

In this paper, an approach for 3D head pose estimation from a monocular sequence is proposed. At the beginning, we employ modified block matching to track face features, including five points (two at inner eyebrow tips, two at eyes and the fifth is nose tip). A matching criterion is designed the effect of matching is improved. To estimate the head pose accurately and simply, we present an algorithm based on the geometry information of the individual face and projective model without the need of any 3D face model and any special marks on user´s face. Any people with different facial characters can be adapted to this algorithm. At the end of this paper, some experimental results and conclusion are given.