Vision threads: a novel approach to generic camera calibration

2021 ◽  
Author(s):  
Shishir Gauchan ◽  
Jonas Bartsch ◽  
Ralf B. Bergmann
Keyword(s):  
Camera Calibration ◽  
Novel Approach ◽  
Generic Camera

scholarly journals LiDAR-Camera Calibration Using Line Correspondences

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6319
Author(s):  
Zixuan Bai ◽  
Guang Jiang ◽  
Ailing Xu
Keyword(s):  
Error Analysis ◽  
Camera Calibration ◽  
Real Data ◽  
Point Clouds ◽  
Translation Vector ◽  
Parallel Lines ◽  
Novel Approach ◽  
Extrinsic Parameters ◽  
On Line ◽  
Data Error

In this paper, we introduce a novel approach to estimate the extrinsic parameters between a LiDAR and a camera. Our method is based on line correspondences between the LiDAR point clouds and camera images. We solve the rotation matrix with 3D–2D infinity point pairs extracted from parallel lines. Then, the translation vector can be solved based on the point-on-line constraint. Different from other target-based methods, this method can be performed simply without preparing specific calibration objects because parallel lines are commonly presented in the environment. We validate our algorithm on both simulated and real data. Error analysis shows that our method can perform well in terms of robustness and accuracy.

scholarly journals AN ITERATIVE APPROACH FOR SELF-CALIBRATING BUNDLE ADJUSTMENT

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 97-102
Author(s):  
J. L. Wang
Keyword(s):  
Camera Calibration ◽  
Measurement Accuracy ◽  
Bundle Adjustment ◽  
Controlled Environment ◽  
Calibration Model ◽  
Iterative Approach ◽  
Virtual Image ◽  
Advantages And Disadvantages ◽  
Novel Approach ◽  
Calibration Models

Abstract. Obtaining accurate image interior and exterior orientations is the key to improve 3D measurement accuracy besides reliable and accurate image matching. A majority of cameras used for those tasks are non-metric cameras. Non-metric cameras commonly suffer various distortions. Generally, there are two ways to remove these distortions: 1) conducting prior camera calibration in a controlled environment; 2) applying self-calibrating bundle adjustment in the application environment. Both approaches have their advantages and disadvantages but one thing is common that there is no universal calibration model available so far which can remove all sorts of distortions on images and systemic errors of image orientations. Instead of developing additional calibration models for camera calibration and self-calibrating adjustment, this paper presents a novel approach which applies self-calibrating bundle adjustment in an iterative fashion: after performing a conventional self-calibrating bundle adjustment, the image coordinates of tie points are re-calculated using the newly obtained self-calibration model coefficients, and the self-calibrating bundle adjustment is applied again in the hope that the remaining distortions and systematic errors will be reduced further within next a few iterations. Using a “virtual image” concept this iterative approach does not require to resample images or/and re-measure tie points during iterations, only costs a few additional iterations computational resource. Several trails under various application environments are conducted using this proposed iterative approach and the results indicate that not only the distortions can be reduced further but also image orientations become much stable after a few iterations.

scholarly journals A NOVEL APPROACH TO CAMERA CALIBRATION METHOD FOR SMART PHONES UNDER ROAD ENVIRONMENT

2016 ◽  
Vol XLI-B5 ◽  
pp. 49-54
Author(s):  
Bijun Lee ◽  
Jian Zhou ◽  
Maosheng Ye ◽  
Yuan Guo
Keyword(s):  
Camera Calibration ◽  
Smart Phone ◽  
Warning System ◽  
Image Data ◽  
Calibration Method ◽  
Smart Phones ◽  
Driver Assistance Systems ◽  
The Road ◽  
Novel Approach ◽  
On The Road

Monocular vision-based lane departure warning system has been increasingly used in advanced driver assistance systems (ADAS). By the use of the lane mark detection and identification, we proposed an automatic and efficient camera calibration method for smart phones. At first, we can detect the lane marker feature in a perspective space and calculate edges of lane markers in image sequences. Second, because of the width of lane marker and road lane is fixed under the standard structural road environment, we can automatically build a transformation matrix between perspective space and 3D space and get a local map in vehicle coordinate system. In order to verify the validity of this method, we installed a smart phone in the ‘Tuzhi’ self-driving car of Wuhan University and recorded more than 100km image data on the road in Wuhan. According to the result, we can calculate the positions of lane markers which are accurate enough for the self-driving car to run smoothly on the road.

A Novel Approach to On-Site Camera Calibration and Tracking for MR Pre-visualization Procedure

2009 ◽  
pp. 492-502 ◽  
Author(s):  
Wataru Toishita ◽  
Yutaka Momoda ◽  
Ryuhei Tenmoku ◽  
Fumihisa Shibata ◽  
Hideyuki Tamura ◽  
...  
Keyword(s):  
Camera Calibration ◽  
Novel Approach

scholarly journals Sub-Pixel Chessboard Corner Localization for Camera Calibration and Pose Estimation

2018 ◽  
Vol 8 (11) ◽  
pp. 2118 ◽  
Author(s):  
Tianlong Yang ◽  
Qiancheng Zhao ◽  
Xian Wang ◽  
Quan Zhou
Keyword(s):  
Camera Calibration ◽  
Pose Estimation ◽  
High Performance ◽  
Vision System ◽  
Low Cost ◽  
Input Image ◽  
Point Problem ◽  
Novel Approach ◽  
Site Use ◽  
Common Vision

This work describes a novel approach to localize sub-pixel chessboard corners for camera calibration and pose estimation. An ideally continuous chessboard corner model is established, as a function of corner coordinates, rotation and shear angles, gain and offset of grayscale, and blurring strength. The ideal model is evaluated by a low-cost and high-similarity approximation for sub-pixel localization, and by performing a nonlinear fit to input image. A self-checking technique is also proposed by investigating qualities of the model fits, for ensuring the reliability of addressing perspective-n-point problem. The proposed method is verified by experiments, and results show that it can share a high performance. It is also implemented and examined in a common vision system, which demonstrates that it is suitable for on-site use.

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