Abstract
Point cloud registration is a key technology in reverse engineering. The registration process of point cloud is divided into coarse registration and fine registration. For fine registration process, ICP (Iterative Close Point) is a classic algorithm. The traditional ICP algorithm is inefficient and incorrect if the correct initial point set is not obtained. In this paper, a point cloud registration algorithm based on 3D-SIFT features is proposed. In this method, the 3D-SIFT algorithm is used to extract key points. At the same time, the 3D-feature descriptor is used as a constraint on the initial set of points in the ICP algorithm. The results show that the method improves the efficiency and precision of the ICP algorithm, and achieves better results of point cloud registration.
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Acknowledgment
We thank the anonymous reviewers for the insightful and constructive comments. This work is in part supported by the Liaoning Province Doctor Startup Fund (No. 201601302).
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Jiao, Z., Liu, R., Yi, P., Zhou, D. (2019). A Point Cloud Registration Algorithm Based on 3D-SIFT. In: Pan, Z., Cheok, A., Müller, W., Zhang, M., El Rhalibi, A., Kifayat, K. (eds) Transactions on Edutainment XV. Lecture Notes in Computer Science(), vol 11345. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-59351-6_3
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DOI: https://doi.org/10.1007/978-3-662-59351-6_3
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