A Target Detection Algorithm for 3D Lidar Point Cloud

Aiming at the problem of accurately detecting targets in real time from the 3D Lidar point cloud, a target detection algorithm based on the features of the scanning line segment is proposed. Firstly; the scanning lines are divided according to the Euclidean distance and vertical height difference between adjacent points. Then analyzes the characteristics of the adjacent line segments, such as pitch, slope, and height difference. Finally, line segments are marked as the ground segments, slope segments and obstacle segments by using Markov random field. The comparison experiments show that this algorithm can accurately segment the ground efficiently.