3D Face Recognition Using Multi-level Multi-feature Fusion

This paper proposed a novel 3D face recognition algorithm using multi-level multi-feature fusions. A new face representation method named average edge image is proposed in addition to traditional ones such as maximal principal curvature image and range image. In the matching process stage, a new weight calculation algorithm based on the sum rule is presented for feature fusion and match score fusion in order to improve the matching precision. Depending on the complementary characteristic of feature fusion and match score fusion, a combination of them named two-level fusion is proposed. Experiments are conducted using our own 3D database consisting of nearly 400 samples. Mesh simplification is utilized for data reduction. Recognition results show that the new weight calculation method improves the recognition accuracy and the two-level fusion algorithm performs better than feature fusion and match score fusion.