Abstract
Abstract. A fundamental task in photogrammetry is the temporal stability analysis of a camera/imaging-system’s calibration parameters. This is essential to validate the repeatability of the parameters’ estimation, to detect any behavioural changes in the camera/imaging system and to ensure precise photogrammetric products. Many stability analysis methods exist in the photogrammetric literature; each one has different methodological bases, and advantages and disadvantages. This paper presents a simple and rigorous stability analysis method that can be straightforwardly implemented for a single camera or an imaging system with multiple cameras. The basic collinearity model is used to capture differences between two calibration datasets, and to establish the stability analysis methodology. Geometric simulation is used as a tool to derive image and object space scenarios. Experiments were performed on real calibration datasets from a dual fluoroscopy (DF; X-ray-based) imaging system. The calibration data consisted of hundreds of images and thousands of image observations from six temporal points over a two-day period for a precise evaluation of the DF system stability. The stability of the DF system – for a single camera analysis – was found to be within a range of 0.01 to 0.66 mm in terms of 3D coordinates root-mean-square-error (RMSE), and 0.07 to 0.19 mm for dual cameras analysis. It is to the authors’ best knowledge that this work is the first to address the topic of DF stability analysis.
Highlights
Stability analysis in this research is aimed at evaluating the stability of calibration parameters of an imaging system
The dual fluoroscopy (DF) system is an X-ray based imaging system used for the six degree-of-freedom human/animal motion analysis
This paper has presented a simple and rigorous stability analysis methodology
Summary
Stability analysis in this research is aimed at evaluating the stability of calibration parameters of an imaging system. Given two sets of calibration parameters (e.g., interior and/or relative orientation parameters, IOPs and ROPs, respectively) from different temporal points, the stability analysis goal is to determine whether or not the two sets are equivalent. Photogrammetric calibration sessions have to be performed to estimate the IOPs and ROPs of the imaging system at different temporal points. The estimated parameters from the different calibration sessions should be compared and qualitatively evaluated. A classical parametrization of a single-camera internalgeometry is established through interior orientation parameters (IOPs), which ideally consist of a principal point (xp, yp) and a principal distance (c) in addition to lens/lenses distortion parameters. A classical parametrization of an imaging system with multiple cameras can be established by a set of IOPs for each individual camera and relative orientation parameters (ROPs) between the different cameras. Each ROP set consists of rotational and directional parameters (e.g., three rotation angles and a 3D translation vector)
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