题目/Title：一种大场景有序点云的快速、准确分割方法
                        A Fast and Accurate Segmentation Method for Ordered Point Cloud of Large-Scale Scenes

作者/Author：朱晓鑫,谢翔,李国林
                        Xiaoxin Zhu,Xiang Xie,Guolin Li

期刊/Journal：微电子学与计算机 Microelectronics & Computer

年份/Issue Date：2016.Nov.

卷（期）及页码/Volume（No.）&pages：Vol.33, No.11, pp. 45 - 49

摘要/Abstract：
针对复杂大场景的点云分割问题，提出了一种快速、准确的分割方法。采用基于扫描线的分割算法，利用点云的有序性和地面几何特征提取地面点，在坡路等复杂地面情况下也能正确分割地面；基于扫描系统的性能确定初始阈值，实现了对非地面点的逐点快速分割；提出了基于体量的自适应算法对过分割的点云进行合并。实验结果表明，在复杂场景下，该分割方法的准确率在90%以上，并且运算复杂度低，逐点处理速度为平均每个点用时14.5微秒，可在点云数据采集过程中进行实时处理。
A fast and accurate segmentation method for point cloud of large-scale scenes is proposed. A scan-line-based ground filter algorithm is designed based on the ordering of point cloud and the geometrical characteristic of the ground, complex ground conditions such as slopes can be handled. Non-ground points are fast segmented point-by-point based on the initial threshold which takes the performance of the scanning system into consideration. Then over-segmented points are merged through the volume-based adaptive algorithm. The accuracy rate of the proposed method is over 90% and the point-by-point processing speed is 14.5 per point, real-time processing can be achieved