Paper Info
Title
Extrinsic calibration of a camera and a lidar based on decoupling the rotation from the translation
Abstract
In this paper, we propose a novel robust algorithm for the extrinsic calibration of a camera and a lidar. This algorithm utilizes checkerboard as a calibration object. Since the interaction between the estimation errors of the plane parameters obtained from checkerboard images downgrades the quality of extrinsic calibration results, a new geometric constraint is presented to decouple the rotation from the translation so as to reduce the effect of such an interaction. Weights that represent uncertainty of the unit normal vector to the checkerboard plane are introduced to totally evaluate the quality of each pair of image and lidar scan. Furthermore, we analyze the configuration of checkerboard pose and give a formula that is used to assess the configuration. We compare the proposed algorithm with the previous ones. Simulation and experimental results show that our algorithm is able to achieve more accurate extrinsic parameters than the existing algorithms. Meanwhile, we also design experiments to validate the effectiveness and efficiency of the presented weight and the assessment formula.
Year
DOI
Venue
2012
10.1109/IVS.2012.6232233
Intelligent Vehicles Symposium
Keywords
Field
DocType
calibration,extrinsic calibration,unit normal vector,estimation errors,camera,robust algorithm,optical radar,checkerboard pose,lidar,cameras,checkerboard images,geometric constraint,calibration object,laser radar,vectors
Computer vision,Computer science,Checkerboard,Decoupling (cosmology),Lidar,Artificial intelligence,Optical radar,Normal,Calibration
Conference
Volume
Issue
ISSN
null
null
1931-0587
ISBN
Citations 
PageRank 
978-1-4673-2119-8
6
0.56
References 
Authors
7
2
Name
Order
Citations
PageRank
Lipu Zhou1255.16
Zhi-Dong Deng219829.50