A Fast Ground Segmentation Method for 3D Point Cloud

Phuong Chu, Seoungjae Cho, Sungdae Sim, Kiho Kwak and Kyungeun Cho
Volume: 13, No: 3, Page: 491 ~ 499, Year: 2017
10.3745/JIPS.02.0061
Keywords: 3D Point Cloud, Ground Segmentation, Light Detection and Ranging, Start-Ground Point, Threshold Point
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Abstract
In this study, we proposed a new approach to segment ground and nonground points gained from a 3D laser range sensor. The primary aim of this research was to provide a fast and effective method for ground segmentation. In each frame, we divide the point cloud into small groups. All threshold points and start- ground points in each group are then analyzed. To determine threshold points we depend on three features: gradient, lost threshold points, and abnormalities in the distance between the sensor and a particular threshold point. After a threshold point is determined, a start-ground point is then identified by considering the height difference between two consecutive points. All points from a start-ground point to the next threshold point are ground points. Other points are nonground. This process is then repeated until all points are labelled

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Cite this article
IEEE Style
Phuong Chu, Seoungjae Cho, Sungdae Sim, Kiho Kwak, Kyungeun Cho, "A Fast Ground Segmentation Method for 3D Point Cloud," Journal of Information Processing Systems, vol. 13, no. 3, pp. 491~499, 2017. DOI: 10.3745/JIPS.02.0061.

ACM Style
Phuong Chu, Seoungjae Cho, Sungdae Sim, Kiho Kwak, Kyungeun Cho, "A Fast Ground Segmentation Method for 3D Point Cloud," Journal of Information Processing Systems, 13, 3, (2017), 491~499. DOI: 10.3745/JIPS.02.0061.