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This paper proposes a coarse-to-fine 3D keypoint detection method based on Principal Component Analysis and Harris operator. At first, the local neighborhood of each vertex is determined according to the conception of "ring". Then the Principal Component Analysis method is performed on the local surface, and the ratio between the first two principal axes of the local neighboring surface is used for selecting candidate keypoints. Finally we compute the Hessian matrix of the local surface throughdoaj:b85f1359023242f5b04b16e1d0effdb1 fatcat:qppgxbjsdjb6lnytp6wtfh7a7q