Fast Ground Segmentation for 3D LiDAR Point Cloud Based on Jump-Convolution-Process

• Published in: Remote sensing (Basel, Switzerland) Vol. 13; no. 16; p. 3239
• Main Authors: Shen, Zhihao, Liang, Huawei, Lin, Linglong, Wang, Zhiling, Huang, Weixin, Yu, Jie
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 15.08.2021
• Subjects: Accuracy; Adaptability; Algorithms; autonomous vehicles; Clouds; Convolution; data collection; Deep learning; Driving ability; Environmental information; Feature extraction; ground segmentation; Image segmentation; landscapes; LiDAR; memory; Methods; Neural networks; Propagation; real-time; Roads & highways; Three dimensional models; Vehicle safety

LiDAR occupies a vital position in self-driving as the advanced detection technology enables autonomous vehicles (AVs) to obtain much environmental information. Ground segmentation for LiDAR point cloud is a crucial procedure to ensure AVs’ driving safety. However, some current algorithms suffer fro...