CAJ | 학술논문

提出了一种基于点云的地平面初系数估测算法。采用八叉树存储包含RGB和空间位置信息点云数据，通过比较相邻两帧树的叶节点来获取运动目标的局部点云。并使用随机采样一致性算法估计，由运动目标局部点云重心所构成的点集上的平面模型参数。同时，采用ISOCLUS算法对场景在法向空间和距离空间上进行两次聚类来分割平面。最终，以运动平面法向信息作为参考因素，从待选平面中标识出地平面点云数据。实验结果显示，该方法可有效地估测出地平面初系数。
제출료일충기우점운적지평면초계수고측산법。채용팔차수존저포함RGB화공간위치신식점운수거，통과비교상린량정수적협절점래획취운동목표적국부점운。병사용수궤채양일치성산법고계，유운동목표국부점운중심소구성적점집상적평면모형삼수。동시，채용ISOCLUS산법대장경재법향공간화거리공간상진행량차취류래분할평면。최종，이운동평면법향신식작위삼고인소，종대선평면중표식출지평면점운수거。실험결과현시，해방법가유효지고측출지평면초계수。
An approach is proposed for estimating initial coefficients of the ground plane with point clouds.The octree used first to store the point clouds that contain RGB and location information.The moving object's partial point clouds can be acquired by comparing leaf nodes of two neighboring frames.Then a set consists of centroids extracted from moving object's partial point clouds is utilized to fit a plane through RANSAC.Besides, clustering is performed on normal and distance space successively by ISOCLUS algorithm to segment planes.Finally, the ground plane is chosen from segmented planes according to normal of the plane of the moving object.This method achieves reliable results for estimating initial coefficients of the ground plane through experiment.