Classification of Point Cloud Using Received Light Intensity According to the Degree of Separation

Yoshitaka Nagai, Ryosuke Kusakari, Yoji Kuroda

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In the conventional intersection recognition method, shape information obtained from 3D LiDAR is used. In order to recognize intersections composed of the road and the others, it is necessary to classify obtained point cloud. However, there is almost no difference in shape between grass and asphalt. For this reason, it is difficult to distinguish them by using the shape information. Therefore, we use received light intensity to broadly classified into grass and asphalt. In this paper, we detect points on the grass by comparing the received light intensity at the equidistant points from the 3D LiDAR. The appropriate threshold for distinguishing materials is automatically calculated for each distance using Discriminant Analysis Method according to validity of classification. Our proposed method will provide that extracting of points on the grass zone is robust and appropriate for the changing reflection intensity of the ground surface.

Original languageEnglish
Title of host publicationProceedings of the 2020 IEEE/SICE International Symposium on System Integration, SII 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages323-328
Number of pages6
ISBN (Electronic)9781728166674
DOIs
Publication statusPublished - Jan 2020
Event2020 IEEE/SICE International Symposium on System Integration, SII 2020 - Honolulu, United States
Duration: 12 Jan 202015 Jan 2020

Publication series

NameProceedings of the 2020 IEEE/SICE International Symposium on System Integration, SII 2020

Conference

Conference2020 IEEE/SICE International Symposium on System Integration, SII 2020
CountryUnited States
CityHonolulu
Period12/01/2015/01/20

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Nagai, Y., Kusakari, R., & Kuroda, Y. (2020). Classification of Point Cloud Using Received Light Intensity According to the Degree of Separation. In Proceedings of the 2020 IEEE/SICE International Symposium on System Integration, SII 2020 (pp. 323-328). [9026219] (Proceedings of the 2020 IEEE/SICE International Symposium on System Integration, SII 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SII46433.2020.9026219