Appearance model based face-to-face transform
Takayuki Nagai, Tuan T. Nguyen · 2004
In this paper, a novel approach to face-to-face transform is presented. The face-to-face transform is a technique, which transforms one person’s facial actions to the others. In gen-eral, the 3D models of faces are used for such transforma-tion. Therefore the facial action parameters should be es-timated from the 2D input images, which is not an easy task. On the contraly, our proposed approach is based on the 2D appearance model instead of the 3D model so that the model is acquired by learning directly from training im-ages. To achieve this, we investigate making use of the Hid-den Markov Model (HMM) framework, which models the correspondence between an input face and the other’s one as well as the appearances of both faces. The experimental results show the effectiveness of the proposed method. 1.