Abstract: An algorithm that can synthesize multi-pose face images from a single view or small samples is proposed in this paper. First, the human face is represented with a dominant point set. Then, the variance of the dominant point set between different poses is fitted based on a least square fitting with a polynomial function and a global morphing field is formed. Finally, multi-pose face images are synthesized by image warping from a single view based on the global morphing field. An experiment of multi-pose face recognition is done based on the single view and synthesized multi-pose images. The results show that its performance is by far superior to those of the traditional methods. Thus, they prove the effectiveness of the algorithm in this paper.