Self-Adaptive 3D Face Recognition Based on Feature Division

The 3D face recognition attracts more and more attention recently, because of its insensitivity to the variance of illumination and pose. In this paper, a novel self-adaptive 3D face recognition algorithm based on face feature division is proposed. This algorithm first divides the 3D face into some block regions based on face features, and then, four face surface characters are extracted for all the block regions to represent the 3D face, and a novel self-adaptive 3D face recognition algorithm is proposed to balance the contributions of all the block regions. After that, a linear weighted strategy is adopted to hybrid the four characters and boost the recognition rate further. Finally, we test our algorithm on BJUT-3D face database and concluded that the performance of our algorithm and fusion strategy is satisfying.