基于单目视觉下的裂缝三向变化检测
Three-dimensional Crack-Change Detection Based on Monocular Vision
刘磊 1丁勇 1李登华2
作者信息
- 1. 南京理工大学物理学院,江苏 南京 210094
- 2. 南京水利科学研究院,江苏 南京 210024;水利部水库大坝安全重点实验室,江苏 南京 210024
- 折叠
摘要
单目视觉测量技术下存在二维图片深度信息缺失,导致无法快速直接测量出二维图像中三维坐标的问题.为在单目视觉下快速利用二维图像直接获取其三维坐标,提出了单目视觉的裂缝三维变化检测方法.根据裂缝变化等效模型设计了特制靶标,利用特征点进行Epnp(efficient perspective-n-point)求解,得到了多次拍摄图片时相机的相对位姿,利用最小二乘法还原其深度信息,通过迭代最近点算法进行坐标系转换,得出了实际的三维位移变化,绝对误差精度在0.5 mm以内,满足工程中对裂缝的检测要求.
Abstract
The depth information of two-dimensional(2D)images cannot be captured via monocular-vision measurement technology,consequently,the three-dimensional(3D)coordinates in the 2D image cannot be measured rapidly and directly.Hence,this paper proposes a 3D crack-change detection method based on monocular vision.Using an equivalent crack-change model,a special target was designed,feature points were used to solve the Epnp(efficient perspective-n-point),the relative pose of the camera during repeated photograph capturing was obtained,the depth information was restored using the least-squares method,and the actual 3D displacement change was obtained using the iterative closest point algorithm for coordinate-system conversion.The absolute-error accuracy was within 0.5 mm,which satisfies the requirements of cracks specified in engineering.
关键词
单目视觉/迭代最近点算法/三维重建/裂缝测量Key words
monocular vision/iterative closest point algorithm/three-dimensional reconstruction/crack measurement引用本文复制引用
基金项目
国家重点研发计划(2022YFC3005502)
国家自然科学基金(51979174)
国家自然科学基金联合基金项目(U2040221)
中央级公益性科研院所基本科研业务费专项资金(Y322008)
出版年
2024
NETL
NSTL
万方数据