Method of 3D face recognition based on keypoint matching
关键点匹配三维人脸识别方法*

This paper proposed a novel algorithm for 3D face recognition based on keypoint matching. Its idea was to rotate each 3D point cloud representing a face around the x, y or z axes, iteratively projecting the 3D points onto 2.5D images. It extracted the keypoints from 2.5D images, set of keypoints replaced the original face scan, performed test faces the same keypoint extraction technique, and secondly using a new weighted keypoint matching algorithm to recognize face. Evaluation using the GavabDB 3D face recognition dataset, the method achieved up to 94% recognition accuracy for faces with neutral expressions, and 88% accuracy for face recognition with expressions (such as a smile).The experiment results show that this method gets remarkable progress in recognizing accuracy.