Efficient generic calibration method for general cameras with single centre of projection

Generic camera calibration is a non-parametric calibration technique that is applicable to any type of vision sensor. However, the standard generic calibration method was developed with the goal of generality and it is therefore sub-optimal for the common case of cameras with a single centre of projection (e.g. pinhole, fisheye, hyperboloidal catadioptric). This paper proposes novel improvements to the standard generic calibration method for central cameras that reduce its complexity, and improve its accuracy and robustness. Improvements are achieved by taking advantage of the geometric constraints resulting from a single centre of projection. Input data for the algorithm is acquired using active grids, the performance of which is characterised. A new linear estimation stage to the generic algorithm is proposed incorporating classical pinhole calibration techniques, and it is shown to be significantly more accurate than the linear estimation stage of the standard method. A linear method for pose estimation is also proposed and evaluated against the existing polynomial method. Distortion correction and motion reconstruction experiments are conducted with real data for a hyperboloidal catadioptric sensor for both the standard and proposed methods. Results show the accuracy and robustness of the proposed method to be superior to those of the standard method

BUILT-IN LENS CORRECTION PROFILES IN LOW-COST CAMERAS: AN ISSUE FOR PHOTOGRAMMETRIC APPLICATIONS?

Photogrammetric applications nowadays envisage the use of more and more low-cost cameras such as those equipped on commercial UAV platforms. Typically, these low-grade cameras suffer from extreme radial distortion and strong vignetting among other defects. This, initiated a trend among the low-cost cameras’ manufacturers to try to hide the camera defects by applying software pre-corrections to the images. These Built-In Correction Profiles gets applied to both the JPG files, directly in-camera, and usually to the raw files as well, through the opcode functions of the DNG standard. In this paper we rise this issue that is still under-reported in the literature and further assess the accuracy implication of applying or discarding the Built-In Correction Profile in the scenario of UAV mapping. We tested the commercial UAV DJI Phantom 4 Pro v2 in a calibration environment and a field test to compare the performance of pre-corrected versus uncorrected images. In our tests, processing the original uncorrected images led to improved IO calibration and reduced bowing effect in the field test

BUILT-IN LENS CORRECTION PROFILES IN LOW-COST CAMERAS: AN ISSUE FOR PHOTOGRAMMETRIC APPLICATIONS?

Photogrammetric applications nowadays envisage the use of more and more low-cost cameras such as those equipped on commercial UAV platforms. Typically, these low-grade cameras suffer from extreme radial distortion and strong vignetting among other defects. This, initiated a trend among the low-cost cameras’ manufacturers to try to hide the camera defects by applying software pre-corrections to the images. These Built-In Correction Profiles gets applied to both the JPG files, directly in-camera, and usually to the raw files as well, through the opcode functions of the DNG standard. In this paper we rise this issue that is still under-reported in the literature and further assess the accuracy implication of applying or discarding the Built-In Correction Profile in the scenario of UAV mapping. We tested the commercial UAV DJI Phantom 4 Pro v2 in a calibration environment and a field test to compare the performance of pre-corrected versus uncorrected images. In our tests, processing the original uncorrected images led to improved IO calibration and reduced bowing effect in the field test

A Full Scale Camera Calibration Technique with Automatic Model Selection – Extension and Validation

This thesis presents work on the testing and development of a complete camera calibration approach which can be applied to a wide range of cameras equipped with normal, wide-angle, fish-eye, or telephoto lenses. The full scale calibration approach estimates all of the intrinsic and extrinsic parameters. The calibration procedure is simple and does not require prior knowledge of any parameters. The method uses a simple planar calibration pattern. Closed-form estimates for the intrinsic and extrinsic parameters are computed followed by nonlinear optimization. Polynomial functions are used to describe the lens projection instead of the commonly used radial model. Statistical information criteria are used to automatically determine the complexity of the lens distortion model. In the first stage experiments were performed to verify and compare the performance of the calibration method. Experiments were performed on a wide range of lenses. Synthetic data was used to simulate real data and validate the performance. Synthetic data was also used to validate the performance of the distortion model selection which uses Information Theoretic Criterion (AIC) to automatically select the complexity of the distortion model. In the second stage work was done to develop an improved calibration procedure which addresses shortcomings of previously developed method. Experiments on the previous method revealed that the estimation of the principal point during calibration was erroneous for lenses with a large focal length. To address this issue the calibration method was modified to include additional methods to accurately estimate the principal point in the initial stages of the calibration procedure. The modified procedure can now be used to calibrate a wide spectrum of imaging systems including telephoto and verifocal lenses. Survey of current work revealed a vast amount of research concentrating on calibrating only the distortion of the camera. In these methods researchers propose methods to calibrate only the distortion parameters and suggest using other popular methods to find the remaining camera parameters. Using this proposed methodology we apply distortion calibration to our methods to separate the estimation of distortion parameters. We show and compare the results with the original method on a wide range of imaging systems