An Acceleration Algorithm of 3D Point Cloud Registration Based on Iterative Closet Point

We propose a novel method for 3D point cloud registration. By considering first order approximation to the data point, our algorithm finds more accurate point pairs than using the closet point strategy. Moreover, we use a new distance error measurement in the ICP framework which considers the second order geometry information rather the first order geometry information in the popular point-plane distance error. Experimental results show that the proposed scheme not only speeds up the convergence of registration, but also eliminates wrong pairing of data points. Both the efficiency of point cloud data registration and the performance of the algorithm have been significantly improved compared with the state-of-the-art methods.