Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

A two-step approach to Lidar-Camera calibration

Su, Yingna ; Ding, Yaqing LU ; Yang, Jian and Kong, Hui (2021) 25th International Conference on Pattern Recognition, ICPR 2020
Abstract
Autonomous vehicles and robots are typically equipped with Lidar and camera. Hence, calibrating the Lidar-camera system is of extreme importance for ego-motion estimation and scene understanding. In this paper, we propose a two-step approach (coarse + fine) for the external calibration between a camera and a multiple-line Lidar. First, a new closed-form solution is proposed to obtain the initial calibration parameters. We compare our solution with the state-of-the-art SVD-based algorithm, and show the benefits of both the efficiency and stability. With the initial calibration parameters, the ICP-based calibration framework is used to register the point clouds which extracted from the camera and Lidar coordinate frames, respectively. Our... (More)
Autonomous vehicles and robots are typically equipped with Lidar and camera. Hence, calibrating the Lidar-camera system is of extreme importance for ego-motion estimation and scene understanding. In this paper, we propose a two-step approach (coarse + fine) for the external calibration between a camera and a multiple-line Lidar. First, a new closed-form solution is proposed to obtain the initial calibration parameters. We compare our solution with the state-of-the-art SVD-based algorithm, and show the benefits of both the efficiency and stability. With the initial calibration parameters, the ICP-based calibration framework is used to register the point clouds which extracted from the camera and Lidar coordinate frames, respectively. Our method has been applied to two Lidar-camera systems: an HDL-64E Lidar-camera system, and a VLP-16 Lidar-camera system. Experimental results demonstrate that our method achieves promising performance and higher accuracy than two open-source methods. (Less)
Please use this url to cite or link to this publication:
author
; ; and
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
International Conference on Pattern Recognition (ICPR)
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
25th International Conference on Pattern Recognition, ICPR 2020
conference location
Virtual, Milan, Italy
conference dates
2021-01-10 - 2021-01-15
external identifiers
  • scopus:85110441538
ISBN
978-1-7281-8809-6
978-1-7281-8808-9
DOI
10.1109/ICPR48806.2021.9412085
language
English
LU publication?
no
id
a78786ac-9a1d-4d64-b474-8c1d87021203
date added to LUP
2022-09-09 10:52:17
date last changed
2025-04-04 14:44:08
@inproceedings{a78786ac-9a1d-4d64-b474-8c1d87021203,
  abstract     = {{Autonomous vehicles and robots are typically equipped with Lidar and camera. Hence, calibrating the Lidar-camera system is of extreme importance for ego-motion estimation and scene understanding. In this paper, we propose a two-step approach (coarse + fine) for the external calibration between a camera and a multiple-line Lidar. First, a new closed-form solution is proposed to obtain the initial calibration parameters. We compare our solution with the state-of-the-art SVD-based algorithm, and show the benefits of both the efficiency and stability. With the initial calibration parameters, the ICP-based calibration framework is used to register the point clouds which extracted from the camera and Lidar coordinate frames, respectively. Our method has been applied to two Lidar-camera systems: an HDL-64E Lidar-camera system, and a VLP-16 Lidar-camera system. Experimental results demonstrate that our method achieves promising performance and higher accuracy than two open-source methods.}},
  author       = {{Su, Yingna and Ding, Yaqing and Yang, Jian and Kong, Hui}},
  booktitle    = {{International Conference on Pattern Recognition (ICPR)}},
  isbn         = {{978-1-7281-8809-6}},
  language     = {{eng}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{A two-step approach to Lidar-Camera calibration}},
  url          = {{http://dx.doi.org/10.1109/ICPR48806.2021.9412085}},
  doi          = {{10.1109/ICPR48806.2021.9412085}},
  year         = {{2021}},
}