FEATURE DETECTION AND CORRESPONDENCE FOR CAMERA CALIBRATION

2008 ◽  
Vol 05 (01) ◽  
pp. 41-50 ◽  
Author(s):  
ZHIGANG ZHENG ◽  
ZHENGJUN ZHA ◽  
LONG HAN ◽  
ZENGFU WANG
Keyword(s):  
Camera Calibration ◽  
Feature Detection ◽  
Checkerboard Pattern ◽  
Geometrical Constraint ◽  
Precise Position ◽  
3D Space ◽  
Corner Points ◽  
Calibration Pattern ◽  
Fully Automatic ◽  
Automatic Camera Calibration

This paper addresses the problem of highly accurate, highly speedy, more reliable and fully automatic camera calibration. Our objective is to construct a reliable and fully automatic system to supply a more robust and highly accurate calibration scheme. A checkerboard pattern is used as calibration pattern. After the corner points on image are detected, an improved Delaunay triangulation based algorithm is used to make correspondences between corner points on image and corner points on checkerboard in 3D space. In order to determine precise position of the actual corner points, a geometrical constraint based global curve fitting algorithm has been developed. The experimental results show that the geometrical constraint based method can improve remarkably the performance of the feature detection and camera calibration.

Research on Fully Automatic Camera Calibration Method

2013 ◽  
Vol 33 (6) ◽  
pp. 0612007 ◽  
Author(s):  
许勇 Xu Yong ◽  
郭鹏宇 Guo Pengyu ◽  
龙古灿 Long Gucan ◽  
张小虎 Zhang Xiaohu ◽  
于起峰 Yu Qifeng
Keyword(s):  
Camera Calibration ◽  
Calibration Method ◽  
Fully Automatic ◽  
Automatic Camera Calibration

A Fully Automatic Camera Calibration Method Based on Planar Target

2014 ◽  
Vol 34 (10) ◽  
pp. 1015004
Author(s):  
卜鹏辉 Bu Penghui ◽  
赵宏 Zhao Hong ◽  
谷飞飞 Gu Feifei ◽  
马跃洋 Ma Yueyang ◽  
李欢欢 Li Huanhuan
Keyword(s):  
Camera Calibration ◽  
Calibration Method ◽  
Planar Target ◽  
Fully Automatic ◽  
Automatic Camera Calibration

scholarly journals Constrained Multiple Planar Reconstruction for Automatic Camera Calibration of Intelligent Vehicles

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4643
Author(s):  
Sang Jun Lee ◽  
Jeawoo Lee ◽  
Wonju Lee ◽  
Cheolhun Jang
Keyword(s):  
Camera Calibration ◽  
Calibration Method ◽  
Image Features ◽  
Intelligent Vehicles ◽  
Point Problem ◽  
Reconstruction Method ◽  
Calibration Methods ◽  
The World ◽  
Extrinsic Parameters ◽  
Automatic Camera Calibration

In intelligent vehicles, extrinsic camera calibration is preferable to be conducted on a regular basis to deal with unpredictable mechanical changes or variations on weight load distribution. Specifically, high-precision extrinsic parameters between the camera coordinate and the world coordinate are essential to implement high-level functions in intelligent vehicles such as distance estimation and lane departure warning. However, conventional calibration methods, which solve a Perspective-n-Point problem, require laborious work to measure the positions of 3D points in the world coordinate. To reduce this inconvenience, this paper proposes an automatic camera calibration method based on 3D reconstruction. The main contribution of this paper is a novel reconstruction method to recover 3D points on planes perpendicular to the ground. The proposed method jointly optimizes reprojection errors of image features projected from multiple planar surfaces, and finally, it significantly reduces errors in camera extrinsic parameters. Experiments were conducted in synthetic simulation and real calibration environments to demonstrate the effectiveness of the proposed method.

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