This paper presents a 3D face recognition technique developed based on the stereovision system. The proposed method first extracts the information of 3D face by means of a stereovision system that restores the 3D information of an object by deriving the disparity of two images, and then uses the principal component analysis algorithm to learn and recognize faces. This research digitizes 120 images, including three face images for each 40 persons, and uses one normal image for training and the other two images for testing. Experimental results show that 87.5% recognition rate is attained with the 3D face information.