@inproceedings{0ffa4134081e4e739920c034dcf8902f,
title = "Robust non-rigid registration algorithm based on local affine registration",
abstract = "Aiming at the problem that the traditional point set non-rigid registration algorithm has low precision and slow convergence speed for complex local deformation data, this paper proposes a robust non-rigid registration algorithm based on local affine registration. The algorithm uses a hierarchical iterative method to complete the point set non-rigid registration from coarse to fine. In each iteration, the sub data point sets and sub model point sets are divided and the shape control points of each sub point set are updated. Then we use the control point guided affine ICP algorithm to solve the local affine transformation between the corresponding sub point sets. Next, the local affine transformation obtained by the previous step is used to update the sub data point sets and their shape control point sets. When the algorithm reaches the maximum iteration layer K, the loop ends and outputs the updated sub data point sets. Experimental results demonstrate that the accuracy and convergence of our algorithm are greatly improved compared with the traditional point set non-rigid registration algorithms.",
keywords = "Iterative closest point, affine registration, hierarchical iteration, non-rigid registration, shape control point",
author = "Liyang Wu and Lei Xiong and Shaoyi Du and Duyan Bi and Ting Fang and Kun Liu and Dongpeng Wu",
note = "Publisher Copyright: {\textcopyright} 2018 SPIE.; 9th International Conference on Graphic and Image Processing, ICGIP 2017 ; Conference date: 14-10-2017 Through 16-10-2017",
year = "2018",
doi = "10.1117/12.2302642",
language = "英语",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Hui Yu and Junyu Dong",
booktitle = "Ninth International Conference on Graphic and Image Processing, ICGIP 2017",
}