摘要
针对整车车身点云空间尺寸较大,数据量庞大,还原精度要求高等特点,提出基于骨架点的点云拼合算法,算法的基本思想是构造整车模型的骨架点和分块点云的mark点,由全等三角形法则搜索骨架点与mark点的映射关系,应用加速迭代的改进ICP(Iterative Closest Point)算法拼合整车点云.某厂轻卡整车点云的拼合实例证明,该算法拼合精度高,运算速度快,是拼合整车点云行之有效的方法.
As the automobiles-bodies point cloud had the traits of large geometric dimension, huge data and rigor reverse precision, one registration and integration algorithm based on the framework points was put forward. The algorithm＇s basic idea is to construct the framework points of vehicle model and the mark points of the separate point cloud, to search the mapped relationship between framework points and mark points using congruence triangle principle and to match the vehicle point cloud using the improved iterative closest point （ICP） algorithm which can accelerate iterative speed. A vehicle point cloud registration example of one light truck proves that this algorithm＇s accuracy on registration is exigent, the calculation speed is very fast and the algorithm is one effective method of matching vehicle body point cloud.
出处
《北京航空航天大学学报》
EI
CAS
CSCD
北大核心
2007年第4期463-466,共4页
Journal of Beijing University of Aeronautics and Astronautics
基金
云南省科技合作计划基金资助项目(2003EAAAAOOD043)
关键词
逆向工程
车身
点云拼合
骨架点
全等三角形
reverse engineering
automobiles-bodies
point cloud registration and integration
framework points
congruence triangle
