This paper presents a novel dynamic face and fingerprint fusion system for identity authentication. To solve the face pose problem in dynamic authentication system, multi-route detection and parallel processing technology are used in this system. A multimodal part face recognition method based on principal component analysis (MMP-PCA) algorithm is adopted to perform the face recognition task. Fusion of face and fingerprint by SVM (Support Vector Machine) fusion strategy which introduced a new normalization method improved the accuracy of identity authentication system. Furthermore, key techniques such as fast and robust face detection algorithm and dynamic fingerprint detection and recognition method based on gray-Level histogram statistic are accepted to guarantee the fast and normal running. Practical results on real database proved that this authentication system can achieve better results compared with face-only or fingerprint-only system. Consequently, this system indeed increases the performance and robustness of identity authentication systems and has more practicability.