Automatic Camera Calibration Using Active Displays of a Virtual Pattern
Camera calibration plays a critical role in 3D computer vision tasks. The most commonly used calibration method utilizes a planar checkerboard and can be done nearly fully automatically. However, it requires the user to move either the camera or the checkerboard during the capture step. This manual...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2017-03-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/17/4/685 |
| _version_ | 1798039440491282432 |
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| author | Lei Tan Yaonan Wang Hongshan Yu Jiang Zhu |
| author_facet | Lei Tan Yaonan Wang Hongshan Yu Jiang Zhu |
| author_sort | Lei Tan |
| collection | DOAJ |
| description | Camera calibration plays a critical role in 3D computer vision tasks. The most commonly used calibration method utilizes a planar checkerboard and can be done nearly fully automatically. However, it requires the user to move either the camera or the checkerboard during the capture step. This manual operation is time consuming and makes the calibration results unstable. In order to solve the above problems caused by manual operation, this paper presents a full-automatic camera calibration method using a virtual pattern instead of a physical one. The virtual pattern is actively transformed and displayed on a screen so that the control points of the pattern can be uniformly observed in the camera view. The proposed method estimates the camera parameters from point correspondences between 2D image points and the virtual pattern. The camera and the screen are fixed during the whole process; therefore, the proposed method does not require any manual operations. Performance of the proposed method is evaluated through experiments on both synthetic and real data. Experimental results show that the proposed method can achieve stable results and its accuracy is comparable to the standard method by Zhang. |
| first_indexed | 2024-04-11T21:53:55Z |
| format | Article |
| id | doaj.art-44f4c69af0c24535b013da4fef16c906 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T21:53:55Z |
| publishDate | 2017-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-44f4c69af0c24535b013da4fef16c9062022-12-22T04:01:10ZengMDPI AGSensors1424-82202017-03-0117468510.3390/s17040685s17040685Automatic Camera Calibration Using Active Displays of a Virtual PatternLei Tan0Yaonan Wang1Hongshan Yu2Jiang Zhu3College of Electrical and Information Engineering, Hunan University, Changsha 410082, ChinaCollege of Electrical and Information Engineering, Hunan University, Changsha 410082, ChinaNational Engineering Laboratory for Robot Visual Perception and Control Technology, Hunan University, Changsha 410082, ChinaCollege of Information Engineering, Xiangtan University, Yuhu District, Xiangtan 411105, ChinaCamera calibration plays a critical role in 3D computer vision tasks. The most commonly used calibration method utilizes a planar checkerboard and can be done nearly fully automatically. However, it requires the user to move either the camera or the checkerboard during the capture step. This manual operation is time consuming and makes the calibration results unstable. In order to solve the above problems caused by manual operation, this paper presents a full-automatic camera calibration method using a virtual pattern instead of a physical one. The virtual pattern is actively transformed and displayed on a screen so that the control points of the pattern can be uniformly observed in the camera view. The proposed method estimates the camera parameters from point correspondences between 2D image points and the virtual pattern. The camera and the screen are fixed during the whole process; therefore, the proposed method does not require any manual operations. Performance of the proposed method is evaluated through experiments on both synthetic and real data. Experimental results show that the proposed method can achieve stable results and its accuracy is comparable to the standard method by Zhang.http://www.mdpi.com/1424-8220/17/4/685camera calibration2D patternactive displaylens distortionclosed-form solutionmaximum likelihood estimation |
| spellingShingle | Lei Tan Yaonan Wang Hongshan Yu Jiang Zhu Automatic Camera Calibration Using Active Displays of a Virtual Pattern Sensors camera calibration 2D pattern active display lens distortion closed-form solution maximum likelihood estimation |
| title | Automatic Camera Calibration Using Active Displays of a Virtual Pattern |
| title_full | Automatic Camera Calibration Using Active Displays of a Virtual Pattern |
| title_fullStr | Automatic Camera Calibration Using Active Displays of a Virtual Pattern |
| title_full_unstemmed | Automatic Camera Calibration Using Active Displays of a Virtual Pattern |
| title_short | Automatic Camera Calibration Using Active Displays of a Virtual Pattern |
| title_sort | automatic camera calibration using active displays of a virtual pattern |
| topic | camera calibration 2D pattern active display lens distortion closed-form solution maximum likelihood estimation |
| url | http://www.mdpi.com/1424-8220/17/4/685 |
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