摘要
针对现有三维重建方法在高速列车车头三维表面重建中存在二义性的问题,提出了一种改进的泊松曲面重建算法来对高速列车车头进行表面三维重建.采用混合滤波器对点云数据进行预处理,采用改进的罚函数对泊松曲面重建算法进行最小化,通过改进阈值法消除等值面提取时的二义性,实现了对高速列车车头表面较为精确的重建.结果证明,该方法具有较高的重构精度与效率,对于高速列车车头的三维重建具有良好的适用性.
Focused on the ambiguity existing in the 3D surface reconstruction for the locomotive of high-speed train using current 3D reconstruction methods,a modified Poisson surface reconstruction algorithm was proposed to carry out the 3D surface reconstruction of the locomotive of high-speed train.Point cloud data were preprocessed with hybrid filter,and the Poisson surface reconstruction algorithm was minimized by an improved penalty function.The ambiguity during equivalent surface extraction was eliminated through an improved threshold method,and a more accurate surface reconstruction for the locomotive of high-speed train was established.The results show that the proposed algorithm possesses higher reconstruction precision and efficiency and good applicability to the 3D reconstruction for the locomotive of high-speed train.
作者
刘长英
王喜超
LIU Chang-ying;WANG Xi-chao(College of Instrumentation Science and Electrical Engineering,Jilin University,Changchun 130061,China)
出处
《沈阳工业大学学报》
EI
CAS
北大核心
2019年第5期529-533,共5页
Journal of Shenyang University of Technology
基金
吉林省科技发展计划项目(20150204053GX)
关键词
高速列车车头
三维重建
隐式曲面函数
泊松曲面重建
点云预处理
算法最小化
罚函数
等值面提取
locomotive of high-speed train
3D reconstruction
implicit surface function
Poisson surface reconstruction
point cloud preprocessing
algorithm minimization
penalty function
equivalent surface extraction
作者简介
刘长英(1974-),男,黑龙江望奎人,副教授,博士,主要从事测控技术与视觉测量技术等方面的研究.
