Study on the camera calibration parameters estimation using the perspective variation ratio

2003 ◽  
Author(s):  
Junik Jeong ◽  
HoSoon Lee ◽  
DoHwan Rho
Keyword(s):  
Camera Calibration ◽  
Parameters Estimation ◽  
Calibration Parameters

The Effect of Noise on Camera Calibration Parameters

2001 ◽  
Vol 63 (5) ◽  
pp. 277-303 ◽  
Author(s):  
Sunil Kopparapu ◽  
Peter Corke
Keyword(s):  
Camera Calibration ◽  
Calibration Parameters

scholarly journals ON-ORBIT GEOMETRIC CALIBRATION APPROACH FOR HIGH-RESOLUTION GEOSTATIONARY OPTICAL SATELLITE GaoFen-4

2016 ◽  
Vol XLI-B1 ◽  
pp. 389-394
Author(s):  
Mi Wang ◽  
Yufeng Cheng ◽  
Xiaoxiang Long ◽  
Bo Yang
Keyword(s):  
Measurement Error ◽  
High Resolution ◽  
Parameters Estimation ◽  
Imaging Features ◽  
Geometric Calibration ◽  
Area Array ◽  
Imaging Model ◽  
Internal Parameters ◽  
Array Camera ◽  
Calibration Parameters

The GaoFen-4 (GF-4) remote sensing satellite is China’s first civilian high-resolution geostationary optical satellite, which has been launched at the end of December 2015. To guarantee the geometric quality of imagery, this paper presents an on-orbit geometric calibration method for the area-array camera of GF-4. Firstly, we introduce the imaging features of area-array camera of GF-4 and construct a rigorous imaging model based on the analysis of the major error sources from three aspects: attitude measurement error, orbit measurement error and camera distortion. Secondly, we construct an on-orbit geometric calibration model by selecting and optimizing parameters of the rigorous geometric imaging model. On this basis, the calibration parameters are divided into two groups: external and internal calibration parameters. The external parameters are installation angles between the area-array camera and the star tracker, and we propose a two-dimensional direction angle model as internal parameters to describe the distortion of the areaarray camera. Thirdly, we propose a stepwise parameters estimation method that external parameters are estimated firstly, then internal parameters are estimated based on the generalized camera frame determined by external parameters. Experiments based on the real data of GF-4 shows that after on-orbit geometric calibration, the geometric accuracy of the images without ground control points is significantly improved.

scholarly journals ON-ORBIT GEOMETRIC CALIBRATION APPROACH FOR HIGH-RESOLUTION GEOSTATIONARY OPTICAL SATELLITE GaoFen-4

2016 ◽  
Vol XLI-B1 ◽  
pp. 389-394 ◽  
Author(s):  
Mi Wang ◽  
Yufeng Cheng ◽  
Xiaoxiang Long ◽  
Bo Yang
Keyword(s):  
Measurement Error ◽  
High Resolution ◽  
Parameters Estimation ◽  
Imaging Features ◽  
Geometric Calibration ◽  
Area Array ◽  
Imaging Model ◽  
Internal Parameters ◽  
Array Camera ◽  
Calibration Parameters

The GaoFen-4 (GF-4) remote sensing satellite is China’s first civilian high-resolution geostationary optical satellite, which has been launched at the end of December 2015. To guarantee the geometric quality of imagery, this paper presents an on-orbit geometric calibration method for the area-array camera of GF-4. Firstly, we introduce the imaging features of area-array camera of GF-4 and construct a rigorous imaging model based on the analysis of the major error sources from three aspects: attitude measurement error, orbit measurement error and camera distortion. Secondly, we construct an on-orbit geometric calibration model by selecting and optimizing parameters of the rigorous geometric imaging model. On this basis, the calibration parameters are divided into two groups: external and internal calibration parameters. The external parameters are installation angles between the area-array camera and the star tracker, and we propose a two-dimensional direction angle model as internal parameters to describe the distortion of the areaarray camera. Thirdly, we propose a stepwise parameters estimation method that external parameters are estimated firstly, then internal parameters are estimated based on the generalized camera frame determined by external parameters. Experiments based on the real data of GF-4 shows that after on-orbit geometric calibration, the geometric accuracy of the images without ground control points is significantly improved.

scholarly journals PRELIMINARY INVESTIGATION INTO THE GEOMETRIC CALIBRATION OF THE MICASENSE REDEDGE-M MULTISPECTRAL CAMERA

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 17-22
Author(s):  
F. Frontera ◽  
M. J. Smith ◽  
S. Marsh
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Camera Calibration ◽  
Low Cost ◽  
Preliminary Investigation ◽  
Distortion Correction ◽  
Geometric Calibration ◽  
Essential Step ◽  
The Past ◽  
Wide Range ◽  
Calibration Parameters

Abstract. Multispectral cameras, in the past the prerogative of Remote Sensing (RS) applications via satellites and manned aircraft, are becoming increasingly used in photogrammetric applications. Moreover, the ubiquitous use of Unmanned Aerial Vehicles (UAVs) has created a need for the miniaturisation of sensors, which has contributed to the availability of a wide range of relatively low-cost and lightweight cameras. Therefore, small multispectral cameras mounted on UAVs provide an effective and low-cost solution when it comes to acquiring airborne radiometric data.With the growing interest for such sensors to perform photogrammetric tasks, camera calibration remains an essential step in order to obtain reliable and geometrically accurate information.This paper will investigate the camera calibration parameters between the five bands of the MicaSense RedEdge-M sensor from laboratory trials. The results of the camera calibration will be obtained from the use, primarily, of Australis software and a calibration frame within the Nottingham Geospatial Institute. The variations of the parameters demonstrate the need for distortion correction separately within each band before using the images for photogrammetry.

scholarly journals Camera parameters estimation from pose detections

2020 ◽  
Vol 44 (3) ◽  
pp. 385-392
Author(s):  
E.A. Shalimova ◽  
E.V. Shalnov ◽  
A.S. Konushin
Keyword(s):  
Computer Vision ◽  
Camera Calibration ◽  
Focal Length ◽  
Parameters Estimation ◽  
Synthetic Dataset ◽  
Orientation Estimation ◽  
Visual Sensors ◽  
Wide Range ◽  
Camera Parameters

Some computer vision tasks become easier with known camera calibration. We propose a method for camera focal length, location and orientation estimation by observing human poses in the scene. Weak requirements to the observed scene make the method applicable to a wide range of scenarios. Our evaluation shows that even being trained only on synthetic dataset, the proposed method outperforms known solution. Our experiments show that using only human poses as the input also allows the proposed method to calibrate dynamic visual sensors.

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