There exist a number of applications that make use of automatic facial expression synthesis and analysis, especially for interaction or communication between human and computers. This paper proposes a novel approach for facial expression synthesis that can generate realistic expressions for a new person with natural expression details. This approach is based on local geometry preserving between the input face image and the target expression image. In order to generate expressions with arbitrary intensity and mixed expression types, this paper also develops an expression analysis scheme based on Supervised Locality Preserving Projections (SLPP) that aligns different subjects and different intensities on a generalized expression manifold. Experimental results demonstrate the effectiveness of the proposed algorithm.