中国激光, 2014, 41 (3): 0314002, 网络出版: 2014-03-03
多传感器点云拼接误差的修正方法
Correction Technique for Joint Error of Multi-Sensor Point Cloud
传感器 误差修正 平移变换 三维人体扫描 sensors error correction translational transformation three-dimensional body scanning
摘要
为了减小激光三维扫描仪多传感器点云拼接误差的影响,提出了一种以圆柱体作为标准物体逐层修正拼接误差的简便方法。对标准物体扫描且拟合出各截面圆心坐标,并利用圆柱体实际半径值求得截面真值圆函数,将每层测量数据向真值圆函数进行平移刚性变换,求得该层的拼接误差和修正值。为了减小随机误差的影响,利用多次重复测量求得平均修正值,并用求出的平均修正值分别对圆柱体、长方棱柱体和石膏人体模特的不同位置的扫描结果进行了修正验证实验。从截面图的直观观察和定量数据测量两方面比较了修正前后的点云拼接效果,结果表明,修正后点云拼接更加光滑平顺,数据测量相对误差有显著降低。
Abstract
In order to reduce the influence of the joint error of three-dimensional (3D) laser scanner′s multi-sensor point cloud, a simple method to correct the joint error layer by layer is presented, which is based on a columnar standard detected object. The standard detected object is scanned, and the scanning data are fitted to get each section′s coordinate of the circle center. The section′s true value circular function is got by using the actual radius of the cylinder. Translational rigid transformation between each layer′s measured data and true value circular function is done to get this layer′s joint error and corrected value. In order to reduce the influence of random error, repeated measurements are done, and the average corrected value is calculated. Then, some verification experiments are conducted on the measured data of cylinder, cuboid and plaster mannequin, which are placed in different locations. The comparison of stitching result between before and after the correction is made from two aspects of ocular observation and quantified data analysis of sampling sections. The results show that the corrected point cloud can joint together more smoothly, and the relative errors of measured data become lower prominently.
杨玉杰, 田庆国, 葛宝臻. 多传感器点云拼接误差的修正方法[J]. 中国激光, 2014, 41(3): 0314002. Yang Yujie, Tian Qingguo, Ge Baozhen. Correction Technique for Joint Error of Multi-Sensor Point Cloud[J]. Chinese Journal of Lasers, 2014, 41(3): 0314002.