A Fast and Accurate Segmentation Method for Ordered LiDAR Point Cloud of Large-Scale Scenes | IEEE Journals & Magazine | IEEE Xplore

A Fast and Accurate Segmentation Method for Ordered LiDAR Point Cloud of Large-Scale Scenes


Abstract:

This letter proposes an efficient two-step segmentation method for large-scale 3-D point cloud data collected by the mobile laser scanners. First, a new scan-line-based g...Show More

Abstract:

This letter proposes an efficient two-step segmentation method for large-scale 3-D point cloud data collected by the mobile laser scanners. First, a new scan-line-based ground segmentation algorithm is designed to filter the points corresponding to the ground with high accuracy. Second, we propose a selfadaptive Euclidean clustering algorithm to further separate the off-ground points corresponding to different objects. Experiments show that our method delivers superior segmentation results on scanned data. In fact, the proposed method can be used in complex scenes including slope and bumpy road at an error rate of 0.674% and a computing throughput of over 20 million points/s.
Published in: IEEE Geoscience and Remote Sensing Letters ( Volume: 11, Issue: 11, November 2014)
Page(s): 1981 - 1985
Date of Publication: 24 April 2014

ISSN Information:


References

References is not available for this document.