How to Build a Curb Dataset with LiDAR Data for Autonomous Driving

• URL: http://arxiv.org/abs/2110.03968v1
• Date: Fri, 8 Oct 2021 08:32:37 GMT
• Title: How to Build a Curb Dataset with LiDAR Data for Autonomous Driving
• Authors: Dongfeng Bai, Tongtong Cao, Jingming Guo and Bingbing Liu
• Abstract summary: Video cameras and 3D LiDARs are mounted on autonomous vehicles for curb detection. Camera-based curb detection methods suffer from challenging illumination conditions. A dataset with curb annotations or an efficient curb labeling approach, hence, is of high demand.
• Score: 11.632427050596728
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Curbs are one of the essential elements of urban and highway traffic environments. Robust curb detection provides road structure information for motion planning in an autonomous driving system. Commonly, video cameras and 3D LiDARs are mounted on autonomous vehicles for curb detection. However, camera-based methods suffer from challenging illumination conditions. During the long period of time before wide application of Deep Neural Network (DNN) with point clouds, LiDAR-based curb detection methods are based on hand-crafted features, which suffer from poor detection in some complex scenes. Recently, DNN-based dynamic object detection using LiDAR data has become prevalent, while few works pay attention to curb detection with a DNN approach due to lack of labeled data. A dataset with curb annotations or an efficient curb labeling approach, hence, is of high demand...

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