The 3D face recognition attracts more and more attention because of its insensitivity to the variance of illumination and pose. There are many crucial problems to be solved in this topic, such as 3D face rcpresentation and effective multi-feature fusion. In this paper, a novel 3D face recognition algorithm is proposed and its performance is demonstrated on BJUT-3D face database. This algorithm choo6es face surface property and the principle component of relative relation matrix as the face representation features. The similarity metric measure for each feature is defined. A feature fusion strategy is proposed. It is a linear weighted strategy based on Fisher linear diseriminant analysis. Finally, the presented algorithm is tested on the BJUT-3D face database. It is concluded that the performance of the algorithm and fusion strategy is satisfying.