A noise-reduction algorithm for raw 3D point cloud data of asphalt pavement surface texture-Reference-Cited by-同舟云学术

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A noise-reduction algorithm for raw 3D point cloud data of asphalt pavement surface texture

Published:2024-07-18 Issue:1 Volume:14 Page:
ISSN:2045-2322
Container-title:Scientific Reports
language:en
Short-container-title:Sci Rep

Author:

Ding Shihai,Chen Xiaoping,Ai Changfa,Wang Jingang,Yang Huaping

Funder

Science and technology project fund of Huzhou Science and Technology Bureau

China Academy of Railway Sciences

Science and Technology Innovation Project in Sichuan Province Housing and Urban-rural Construction Field

Publisher

Springer Science and Business Media LLC

Link

https://www.nature.com/articles/s41598-024-65233-8.pdf

Reference35 articles.

1. Wang, Y. et al. Point cloud and visual feature-based tracking method for an augmented reality-aided mechanical assembly system. Int. J. Adv. Manuf. Technol. 99(9–12), 2341–2352. https://doi.org/10.1007/s001170-018-2575-8 (2018).

2. Mahmood, B., Han, S. U. & Lee, D. E. BIM-based registration and localization of 3D point clouds of indoor scenes using geometric features for augmented reality. Remote Sens. 12(14), 2302. https://doi.org/10.33990/rs12142302 (2020).

3. Zermas, D., Izzat, I. & Papanikolopoulos, N. Fast segmentation of 3D point clouds: A paradigm on LiDAR data for autonomous vehicle application. In 2017 IEEE International Conference on Robotics and Automation, May 29-June 3, 2017, Singapore, 5067–5073. https://doi.org/10.1109/ICRA.2017.7989591 (IEEE, 2017).

4. Zhang, A. A. et al. Intelligent pixel-level detection of multiple distresses and surface design features on asphalt pavements. Comput-Aided Civil Infrastruct. Eng. 37(13), 1654–1673 (2022).

5. Mataei, B., Nejad, F. M. & Zakeri, H. Automatic pavement texture measurement using a new 3D image-based profiling system. Measurement 199(10), 111456 (2022).

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