3D face recognition has become one of the most active research topics in face recognition due to its robustness in the variation on pose and illumination. 3D database is the basis of this work. Design and construction of the face database mainly include acquisition of prototypical 3D face data, preprocessing and standardizing of the data and the structure design. Currently, BJUT-3D database is the largest Chinese 3D face database in the world. It contains 1200 Chinese 3D face images and provides both the texture and shape information of human faces. This data resource plays an important role in 3D face recognition and face model. In this paper, the data description, data collection schema and the post-processing methods are provided to help using the data and future extension. A 3D face data dense correspondence method is introduced. Dense correspondence means that the key facials points are carefully labeled and aligned among different faces, which can be used for a broad range of face analysis tasks. As an application, a pose estimation and face recognition algorithm across different poses is proposed. Eexpremental results show that the proposed algorithm has a good performance.