Automatic Camera Calibration in Close Range Photogrammetry

Abstract

Automatic camera calibration via self-calibration with the aid of coded targets is now very much the norm in closerange photogrammetry. This is irrespective of whether the cameras to be calibrated are high-end metric, or the digital SLRs and consumer-grade models that are increasingly being employed for image-based 3D measurement. Automation has greatly simplified the calibration task, but there are real prospects that important camera calibration issues may be overlooked in what has become an almost black-box operation. This paper discusses the impact of a number of such issues, some of which relate to the functional model adopted for self-calibration, and others to practical aspects which need to be taken into account when pursuing optimal calibration accuracy and integrity. Issues discussed include interior orientation stability, calibration reliability, focal plane distortion, image point distribution, variation in lens distortion with image scale, colour imagery and chromatic aberration, and whether 3D object space control is warranted. By appreciating and accounting for these issues, users of automatic camera calibration will enhance the prospect of achieving an optimal recovery of scene-independent camera calibration parameters.Unfortunately, the vast majority of cameras utilised today for moderate-accuracy close-range 3D measurement were not designed with photogrammetric accuracy in mind, so whereas it is certainly true that off-the-shelf digital cameras ranging from inexpensive consumer-grade to high-end prosumer-grade digital SLRs can be readily applied to photogrammetric measurement, their metric performance is generally well below the level that would be anticipated if the cameras were indeed fully 'metric'. One could say that this is due to a shortcoming in calibration, but as this paper will endeavour to illustrate, it is not so much the process of automated calibration that is deficient, but the nature of the cameras and shortcomings in the imaging networks employed.

Comparison of pre- and self-calibrated camera calibration models for UAS-derived nadir imagery for a SfM application

“…Self-calibration usually achieves the goal of solving the parameters of the Brown distortion model (Fryer and Brown, 1986). To solve a full Brown distortion model, a total of 10 parameters must be computed (Fraser, 2013). However, rigorous results are only possible when the image networks are highly redundant with strong convergent geometry.…”

A Flexible, Generic Photogrammetric Approach to Zoom Lens Calibration

“…Moreover, the use of a 3D test field or a regular 3D object provides advantages for the recovery of the camera model [35], though it has limitations in terms of DOF [34], as well as potential difficulties in automatically extracting and encoding target points due to occlusion. As a result, zoom lens calibration using a planar reference is a cost-effective and flexible proposition.…”

Calibration of Panoramic Cameras With Coded Targets and a 3d Calibration Field

“…These 2D calibration fields are much easier to establish but have some limitations in the case of calibration of omindirecitonal systems. Also, the existing correlations in the parameters to be estimated with bundle adjustment can be reduced when using 3D calibration fields (Fraser, 2013).…”