Registration of ski resort point cloud based on improved algorithm of principal component analysis

Wenxin Wang; Changming Zhao; Haiyang Zhang

doi:10.1117/12.2666769

4 April 2023 Registration of ski resort point cloud based on improved algorithm of principal component analysis

Wenxin Wang, Changming Zhao, Haiyang Zhang

Proceedings Volume 12617, Ninth Symposium on Novel Photoelectronic Detection Technology and Applications; 1261772 (2023) https://doi.org/10.1117/12.2666769
Event: 9th Symposium on Novel Photoelectronic Detection Technology and Applications (NDTA 2022), 2022, Hefei, China

Abstract

Based on the improved algorithm of principal component analysis, we propose a ski resort point cloud registration method to overcome the low precision and lengthy registration process of ski resort point clouds. A Euclidean distance between the normal vectors of the snow field point cloud and an angle between the normal vectors are used to determine the feature points. The matching point set and corresponding pairing relationship are then calculated based on the feature, the point histogram, and the principal component analysis algorithm. The coarse registration is completed by combining the unit quaternion method. Also, the KD tree is utilized to aid in the iterative process of the ICP algorithm and to complete the fine registration of the point cloud data in the snowfield. Comparing the proposed new algorithm with NDT and ICP algorithms, the proposed new algorithm has significantly improved speed and accuracy in registering point clouds in snow fields.

Citation Download Citation

Wenxin Wang, Changming Zhao, and Haiyang Zhang "Registration of ski resort point cloud based on improved algorithm of principal component analysis", Proc. SPIE 12617, Ninth Symposium on Novel Photoelectronic Detection Technology and Applications, 1261772 (4 April 2023); https://doi.org/10.1117/12.2666769

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