The Analysis of Stereo Vision 3D Point Cloud Data of Autonomous Vehicle Obstacle Recognition

Li Pei, Zhou Rui
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引用次数: 4

Abstract

In order to solve the problem of 3D point cloud data interpretation for the autonomous vehicle avoidance system, based on the analysis of the characteristics of the point cloud data, an analysis method of point grid projection is presented in this paper. This method can effectively obtain the interpretation of the road obstacles from the point cloud data. In this paper, the error and independent point was first analyzed and filtered out. Then road area of interest is divided into grid. Useful points are projected onto the grid and the projection effect would give a comprehensive criterion for interpretation, and location of the road obstacles. The method is verified by experiments and the experimental results show that, this method can effectively assist the autonomous vehicle navigation system to determine the obstacles.
自动驾驶汽车障碍物识别的立体视觉三维点云数据分析
为了解决自动驾驶车辆避让系统的三维点云数据解译问题,在分析点云数据特征的基础上,提出了一种点网格投影分析方法。该方法可以有效地从点云数据中获得道路障碍物的解释。本文首先对误差和独立点进行了分析和滤除。然后将感兴趣的道路区域划分为网格。有用的点被投影到网格上,投影效果将为道路障碍物的解释和定位提供一个全面的标准。通过实验验证了该方法的有效性,实验结果表明,该方法能够有效地辅助自动驾驶车辆导航系统对障碍物进行识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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