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作 者:刘长英[1] 王喜超 LIU Chang-ying;WANG Xi-chao(College of Instrumentation Science and Electrical Engineering,Jilin University,Changchun 130061,China)
机构地区:[1]吉林大学仪器科学与电气工程学院
出 处:《沈阳工业大学学报》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)
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.
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