Abstract
A method for 3D face recognition based on Cascade Classifier algorithm is proposed in this paper. First, 3D point data is mapped to X-Y planar by using iteration interpolation method, and the range image is obtained. Then the principal component analysis (PCA) is used to find a low dimensional feature face space and then we achieve match score in accordance with the nearest neighbor rule. Finally, the remaining part faces are verified based on Hausdorff distance algorithm. The simulation experiment is done on CASIA database, the result shows that the performance of our algorithm has some improvement compared with other algorithms.
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