ICP Algorithm

For 3D registration of point sets of an object, we need point sets from at least two different points of view. And the merging process is needed. A popular approach to this process is Iterative Closest Point (ICP) algorithm introduced by Besl [1]. I improved basic ICP algorithm by T. Suguihara's LM method [4] based on A. W. Fitzgibbon's paper [2]. And the results of my ICP algorithm is in section 2. Now, I continuously try to improve this algorithm by searching others paper and from my idea.

Discussion of the detailed process and results is in my report [5].

(All users can view my Report by click the reference [5].)

[1] P. J. Besl, N. McKay, A method for registration od 3-D shapes, IEEE Transactions on Pattern Analysis and Machine Intelligence 14 (2) (1992) 239 - 256.

[2] A. W. Fitzgibbon, Robust registration of 2D and 3D point sets, Image Vision Computing., vol. 21, no. 13–14, pp. 1145–1153, 2003.

[3] S. K. Chan and P. D. Lawrence, "General inverse kinematics with the error damped pseudoinverse," Proceedings. 1988 IEEE International Conference on Robotics and Automation, pp. 834-839 vol.2, 1988.

[4] T. Sugihara, "Solvability-Unconcerned Inverse Kinematics by the Levenberg–Marquardt Method," in IEEE Transactions on Robotics, vol. 27, no. 5, pp. 984-991, Oct. 2011.

[5] Jae Hoon An, "ICP algorithm", Jun. 2021.

[6] 3D data : "Stanford Bunny" @ Stanford University Computer Graphics Laboratory