首页> 外文会议>Asian conference on remote sensing;ACRS >POLE-LIKE ROADSIDE OBJECTS EXTRACTION FROM MOBILE LIDAR POINT CLOUDS
【24h】

POLE-LIKE ROADSIDE OBJECTS EXTRACTION FROM MOBILE LIDAR POINT CLOUDS

机译:从移动激光雷达点云中提取类似道路的道路障碍物

获取原文

摘要

Mobile lidar system can acquire very dense and accurate 3-D point clouds along the road corridors. The acquiring data can provide plentiful road information such as road surface, road marks and road objects. It can be applied on a detailed 3-D road model reconstruction. The objective of this research is to develop automatic process for pole-like objects extraction from mobile lidar data. The major work includes area of interest (AOI) selection, segmentation, initial detection, features recognition and RANdom SAmple Consensus (RANSAC) pole detection. The test data is acquired by Riegl VMX-250 mobile lidar system. The test area is located at Chiu-Chung Road in Taipei city, Taiwan. The length of the test area is about 220 meters. The correctness of objects detection is about 70%. The mean error of x, y, and z coordinates objects are 0.012, 0.009, and 0.039 meters respectively. The mean error of radius is 0.011 meters. With the position and direction of objects, the extracted results can be placed in a LOD3 road model. The experimental results indicate that the proposed process may extract pole-like roadside objects effectively.
机译:移动激光雷达系统可以沿道路走廊获取非常密集且精确的3-D点云。采集数据可以提供丰富的道路信息,例如路面,道路标记和道路物体。它可以应用于详细的3D道路模型重建。这项研究的目的是开发一种自动过程,用于从移动激光雷达数据中提取类似杆的物体。主要工作包括感兴趣区域(AOI)的选择,分割,初始检测,特征识别和RANDOM SAmple Consensus(RANSAC)极点检测。测试数据通过Riegl VMX-250移动激光雷达系统获取。测试区域位于台湾台北市潮中路。测试区域的长度约为220米。物体检测的正确性约为70%。 x,y和z坐标对象的平均误差分别为0.012、0.009和0.039米。半径的平均误差为0.011米。通过对象的位置和方向,可以将提取的结果放置在LOD3道路模型中。实验结果表明,该方法可以有效地提取杆状路边物体。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号