Automatic ground points filtering of roadside LiDAR data using a channel-based filtering algorithm. (July 2019)

• Record Type: Journal Article
• Authors: Wu, Jianqing; Tian, Yuan; Xu, Hao; Yue, Rui; Wang, Aobo; Song, Xiuguang
• Is Part Of: Optics & laser technology. Volume 115(2019)
• Page Start: 374
• Page End: 383
• Publication Date: 2019-07
• Subjects: Ground surface -- Roadside LiDAR -- Object classification; Optics -- Periodicals; Lasers -- Periodicals; Electronic journals; 621.366
• DOI: 10.1016/j.optlastec.2019.02.039
• Languages: English
• ISSNs: 0030-3992

Abstract

Highlights: An automatic ground points exclusion method was developed. Channel Information was used for analysis. The method accommodates the different types of the LiDAR. Abstract: Ground points information is valuable for various transportation applications. To date, limited studies have been applied for ground points identification with the roadside LiDAR sensor. This paper presents an innovative approach to extract the ground points for the roadside LiDAR effectively. The proposed method can be divided into four major parts: region of intersection (ROI) Selection, background filtering, channel-based clustering, and slope-based filtering. The channel information is used for the ground points extraction. Data collected at different scenarios were used to evaluate the performance of the proposed method. It was shown that the algorithm can successfully extract ground points regardless of slope on the road and package loss issue. The developed method can also accommodate the different types of the LiDAR. Compared to the state-of-the-art methods, the overall performance of the proposed method is superior.