Raster-Based Background Filtering for Roadside LiDAR Data
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Authors
Lv, Bin
Xu, Hao
Wu, Jianqing
Tian, Yuan
Yuan, Changwei
Issue Date
2019
Type
Article
Language
Keywords
Background filtering , connected-vehicles , roadside LiDAR
Alternative Title
Abstract
The roadside deployed light detecting and ranging (LiDAR) has been a solution to fill the data gap for the transition period from the unconnected-vehicles environment to the connected-vehicles system. For the roadside LiDAR system, background filtering is an initial but important step. This paper presented a raster-based method for background filtering with roadside LiDAR data. The proposed method contains four major parts: region of interest (ROI) selection, rasterization, background area detection, and background array generation. The location of the background points was stored in a 3D array. The performance of the raster-based method was tested with the data collected at different scenarios. The comparison to the stateof-the-art also confirmed the robustness of the proposed method.
Description
Citation
Lv, B., Xu, H., Wu, J., Tian, Y., & Yuan, C. (2019). Raster-Based Background Filtering for Roadside LiDAR Data. IEEE Access, 7, 76779�"76788. doi:10.1109/access.2019.2919624
Publisher
License
Open Access
Journal
Volume
Issue
PubMed ID
ISSN
2169-3536