扰动(地质)
点云
直线(几何图形)
点(几何)
计算机科学
运动(物理)
控制理论(社会学)
计算机视觉
人工智能
数学
地质学
几何学
控制(管理)
古生物学
作者
Luyao Ma,Jigui Zhu,Linghui Yang,Haoyue Liu,Yiyuan Fan,Shuo Yang
出处
期刊:Measurement
[Elsevier]
日期:2024-04-06
卷期号:231: 114669-114669
被引量:4
标识
DOI:10.1016/j.measurement.2024.114669
摘要
In-motion three-dimensional (3-D) shape measurement with dense point cloud is widely required, and line-scan cameras are promising with the advantage of high-frequency high-resolution measurement. However, line-scan camera measurement lacks constraints in point cloud stitching direction and dynamic disturbance in motion distorts the stitched point cloud if there's no precise guide rail. Point cloud optimization remains a challenge and the applications of line-scan cameras hit a bottleneck. In this work, accurate line-scan 3-D measurement is achieved despite dynamic disturbance. Instantaneous two-dimensional imaging of an attached area-scan camera provides constraints for line-scan point cloud profiles, and algorithms are proposed for effective matching and optimization. Local continuity constraints are further utilized for comprehensive line-scan point cloud optimization. Through quantitative and qualitative evaluations, the reconstruction accuracy is significantly improved in motion with dynamic disturbance. The proposed method promotes the application of line-scan cameras and solves a significant challenge in 3-D shape measurement in motion.
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