Browse > Article
http://dx.doi.org/10.3745/KTSDE.2019.8.2.89

Calibration of VLP-16 Lidar Sensor and Vision Cameras Using the Center Coordinates of a Spherical Object  

Lee, Ju-Hwan (경북대학교 컴퓨터학부)
Lee, Geun-Mo (경북대학교 컴퓨터학부)
Park, Soon-Yong (경북대학교 컴퓨터학부)
Publication Information
KIPS Transactions on Software and Data Engineering / v.8, no.2, 2019 , pp. 89-96 More about this Journal
Abstract
360 degree 3-dimensional lidar sensors and vision cameras are commonly used in the development of autonomous driving techniques for automobile, drone, etc. By the way, existing calibration techniques for obtaining th e external transformation of the lidar and the camera sensors have disadvantages in that special calibration objects are used or the object size is too large. In this paper, we introduce a simple calibration method between two sensors using a spherical object. We calculated the sphere center coordinates using four 3-D points selected by RANSAC of the range data of the sphere. The 2-dimensional coordinates of the object center in the camera image are also detected to calibrate the two sensors. Even when the range data is acquired from various angles, the image of the spherical object always maintains a circular shape. The proposed method results in about 2 pixel reprojection error, and the performance of the proposed technique is analyzed by comparing with the existing methods.
Keywords
Calibration; Lidar Sensor; Vision Camera; Spherical Object;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 M. Hassanein, A. Moussa, and N. El-Sheimy, "A new automatic system calibration of multi-cameras and lidar sensors," International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, Vol.41, No. 23, pp.589-594, Jul. 2016.
2 I. Ashraf, S. J. Hur, and Y. W. Park, "An investigation of interpolation techniques to generate 2D intensity images from lidar data," IEEE Access, Vol.5, pp. 8250-8260, Apr. 2017.   DOI
3 J. P. Hwang, S. K. Park, E. T. Kim, and H. J. Kang, "Camera and LIDAR Combined System for On-Road Vehicle Detection," Journal of Institute of Control, Robotics and Systems, Vol.15, No.4, pp.390-395, Oct. 2017.   DOI
4 J. W. Kim, J. Y. Jeong, Y. S. Shin, Y. G. Cho, H. C. Roh, and A. Y. Kim, "Lidar configuration comparison for urban mapping system," 2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence(URAI), pp. 854-857, 2017.
5 Z. Zhang, "A flexible new technique for camera calibration," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.22, No.11, pp.1330-1334, Nov. 2016.   DOI
6 O. Naroditsky, A. Patterson and K. Daniilidis, "Automatic alignment of a camera with a line scan lidar system," 2011 IEEE International Conference on Robotics and Automation (ICRA), pp.3429-3434, 2011.
7 Y. S. Park, S. M. Yun, S. W. Chee, K. E. Cho, K. H. Um, and S. D. Sim, "Calibration between color camera and 3D lidar instruments with a polygonal planar board," Sensors, Vol.14, No.3, pp.5533-5353, Mar. 2014.
8 M. Velas, M. Spanel, Z. Materna, and A. Herout, "Calibration of RGB camera With velodyne lidar," International Conference on Computer Graphics, Visualization and Computer Vision (WSCG), pp.135-144, 2014.
9 T. GEE, J. James, W. V. D. Mark, A. G. Strozzi, P. Delmas, and G. Gimelfarb, "Estimating extrinsic parameters between a stereo rig and a multi-layer lidar using plane matching and circle feature extraction," 2017 Fifteenth IAPR International Conference on Machine Vision Applications(MVA), pp.21-24, 2017.
10 S. Park and S. Choi, "Convenient View Calibration of Multiple RGB-D Cameras Using a Spherical Object," KIPS Transactions on Software and Data Engineering, Vol.3, No.8, pp.309-314, 2014.   DOI
11 G. Lee, J. Lee, and S. Park, "Calibration of VLP-16 Lidar and multi-view cameras using a ball for 360 degree 3D color map acquisition," in Proceedings of 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems(MFI), 2017.
12 J. H. Lee, E. S. Kim, and S. Y. Park, "Synchronization error compensation of multi-view RGB-D 3D modeling system," Asian Conference on Computer Vision(ACCV), pp.162-174, 2016.
13 M. A. Fischler and C. R. Bolles, "Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography," Communications of the ACM, Vol.24, No.6, pp.381-395, Jun. 1981.   DOI
14 M. Ruan and D. Huber, "Calibration of 3D Sensors Using a Spherical Target," 2014 2nd International Conference on 3D Vision, Vol.1, pp.187-193, Dec. 2014.
15 D. Loannou, H. Walter, and A. F. Laine, "Circle recognition through a 2D Hough Transform and radius histogramming," Image and Vision Computing, pp.15-26, 1999.