A novel calibration method for a large-scale stereo vision sensor based on a one-dimensional target

Author(s):  
Ziyan Wu ◽  
Junhua Sun ◽  
Qianzhe Liu ◽  
Guangjun Zhang
2013 ◽  
Vol 33 (3) ◽  
pp. 0315001
Author(s):  
刘震 Liu Zhen ◽  
尚砚娜 Shang Yanna

2019 ◽  
Vol 16 (6) ◽  
pp. 172988141989351
Author(s):  
Xi Zhang ◽  
Yuanzhi Xu ◽  
Haichao Li ◽  
Lijing Zhu ◽  
Xin Wang ◽  
...  

For the purpose of obtaining high-precision in stereo vision calibration, a large-size precise calibration target, which can cover more than half of the field of view is vital. However, large-scale calibration targets are very difficult to fabricate. Based on the idea of error tracing, a high-precision calibration method for vision system with large field of view by constructing a virtual 3-D calibration target with a laser tracker was proposed in this article. A virtual 3-D calibration target that covers the whole measurement space can be established flexibly and the measurement precision of the vision system can be traceable to the laser tracker. First, virtual 3-D targets by calculating rigid body transformation with unit quaternion method were constructed. Then, the high-order distortion camera model was taken into consideration. Besides, the calibration parameters were solved with Levenberg–Marquardt optimization algorithm. In the experiment, a binocular stereo vision system with the field of view of 4 × 3 × 2 m3 was built for verifying the validity and precision of the proposed calibration method. It is measured that the accuracy with the proposed method can be greatly improved comparing with traditional plane calibration method. The method can be widely used in industrial applications, such as in the field of calibrating large-scale vision-based coordinate metrology, and six-degrees of freedom pose tracking system for dimensional measurement of workpiece, as well as robotics geometrical accuracy detection and compensation.


2011 ◽  
Vol 317-319 ◽  
pp. 397-400
Author(s):  
Gang Chen ◽  
Hua Chen ◽  
Yu Bo Guo ◽  
Dong Ye

This paper presents and comparison two stereo vision sensor calibration methods: Volume template based calibration method and the calibration based on virtual stereo pattern. First method use a premade volume template. Second method use a group of random spatial points that are formed by an infrared LED moved with the probe of CMM. Two methods adopt an ideal pin-hole model that ignores the nonlinear distortion of the cameras. Through compare two calibratioin methods, we can draw conclusion that the first method can be applide to stereo sensor calibration in measurement field and the second method could gain higher calibrating precision.


2011 ◽  
Vol 49 (11) ◽  
pp. 1245-1250 ◽  
Author(s):  
Junhua Sun ◽  
Qianzhe Liu ◽  
Zhen Liu ◽  
Guangjun Zhang

2021 ◽  
Vol 187 ◽  
pp. 106237
Author(s):  
Mingyou Chen ◽  
Yunchao Tang ◽  
Xiangjun Zou ◽  
Zhaofeng Huang ◽  
Hao Zhou ◽  
...  

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 44354-44362
Author(s):  
Mingwei Shao ◽  
Pan Wang ◽  
Yanjun Wang

Author(s):  
Chun Xie ◽  
Hidehiko Shishido ◽  
Yoshinari Kameda ◽  
Kenji Suzuki ◽  
Itaru Kitahara

2016 ◽  
Vol 10 (6) ◽  
pp. 2693-2719 ◽  
Author(s):  
Antoine Marmy ◽  
Jan Rajczak ◽  
Reynald Delaloye ◽  
Christin Hilbich ◽  
Martin Hoelzle ◽  
...  

Abstract. Permafrost is a widespread phenomenon in mountainous regions of the world such as the European Alps. Many important topics such as the future evolution of permafrost related to climate change and the detection of permafrost related to potential natural hazards sites are of major concern to our society. Numerical permafrost models are the only tools which allow for the projection of the future evolution of permafrost. Due to the complexity of the processes involved and the heterogeneity of Alpine terrain, models must be carefully calibrated, and results should be compared with observations at the site (borehole) scale. However, for large-scale applications, a site-specific model calibration for a multitude of grid points would be very time-consuming. To tackle this issue, this study presents a semi-automated calibration method using the Generalized Likelihood Uncertainty Estimation (GLUE) as implemented in a 1-D soil model (CoupModel) and applies it to six permafrost sites in the Swiss Alps. We show that this semi-automated calibration method is able to accurately reproduce the main thermal condition characteristics with some limitations at sites with unique conditions such as 3-D air or water circulation, which have to be calibrated manually. The calibration obtained was used for global and regional climate model (GCM/RCM)-based long-term climate projections under the A1B climate scenario (EU-ENSEMBLES project) specifically downscaled at each borehole site. The projection shows general permafrost degradation with thawing at 10 m, even partially reaching 20 m depth by the end of the century, but with different timing among the sites and with partly considerable uncertainties due to the spread of the applied climatic forcing.


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