Result Details

CNN for Very Fast Ground Segmentation in Velodyne LiDAR Data

VEĽAS, M.; ŠPANĚL, M.; HRADIŠ, M.; HEROUT, A. CNN for Very Fast Ground Segmentation in Velodyne LiDAR Data. In IEEE International Conference on Autonomous Robot Systems and Competitions. Torres Vedras: Institute of Electrical and Electronics Engineers, 2018. p. 97-103. ISBN: 978-1-5386-5221-3.
Type
conference paper
Language
English
Authors
Veľas Martin, Ing., Ph.D., DCGM (FIT)
Španěl Michal, doc. Ing., Ph.D., DCGM (FIT)
Hradiš Michal, Ing., Ph.D., DCGM (FIT)
Herout Adam, prof. Ing., Ph.D., DCGM (FIT)
Abstract

This paper presents a novel method for ground segmentation in Velodyne point clouds. We propose an encoding of sparse 3D data from the Velodyne sensor suitable for training a convolutional neural network (CNN). This general purpose approach is used for segmentation of the sparse point cloud into ground and non-ground points. The LiDAR data are represented as a multi-channel 2D signal where the horizontal axis corresponds to the rotation angle and the vertical axis represents channels - laser beams. Multiple topologies of relatively shallow CNNs (i.e. 3-5 convolutional layers) are trained and evaluated, using a manually annotated dataset we prepared. The results show significant improvement of performance over the state-of-the-art method by Zhang et al. in terms of speed and also minor improvements in terms of accuracy.

Keywords

convolutional neural networks, ground segmentation, Velodyne, LiDAR

URL
Published
2018
Pages
97–103
Proceedings
IEEE International Conference on Autonomous Robot Systems and Competitions
Conference
2018 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARS)
ISBN
978-1-5386-5221-3
Publisher
Institute of Electrical and Electronics Engineers
Place
Torres Vedras
DOI
10.1109/ICARSC.2018.8374167
UT WoS
000435384800018
EID Scopus
2-s2.0-85048858816
BibTeX 
@inproceedings{BUT157178,
  author="Martin {Veľas} and Michal {Španěl} and Michal {Hradiš} and Adam {Herout}",
  title="CNN for Very Fast Ground Segmentation in Velodyne LiDAR Data",
  booktitle="IEEE International Conference on Autonomous Robot Systems and Competitions",
  year="2018",
  pages="97--103",
  publisher="Institute of Electrical and Electronics Engineers",
  address="Torres Vedras",
  doi="10.1109/ICARSC.2018.8374167",
  isbn="978-1-5386-5221-3",
  url="https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8374167"
}
Files
Projects
IT4Innovations excellence in science, MŠMT, Národní program udržitelnosti II, LQ1602, start: 2016-01-01, end: 2020-12-31, completed
Transfer of knowledge in the field of 3D reconstruction and 3D mapping, EU, OP PIK - Partnerství znalostního transferu, start: 2017-01-01, end: 2018-09-30, completed
V3C - Visual Computing Competence Center, TAČR, Centra kompetence, TE01020415, start: 2012-05-01, end: 2019-12-31, completed
Zpracování, zobrazování a analýza multimediálních a 3D dat, BUT, Vnitřní projekty VUT, FIT-S-17-3984, start: 2017-03-01, end: 2020-02-29, completed
Research groups
Computer Graphics Research Group (RG GRAPH)
Robotic research group Robo@FIT (RG ROBO)
Departments
Department of Computer Graphics and Multimedia (DCGM)
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