Evaluation of a drone-based camera calibration approach for hard-to-reach cameras

Several applications of video rely on camera calibration, a key enabler towards the measurement of metric parameters from images. Existing calibration methods have not been adapted for use with cameras that are hard to reach such as security cameras. This paper presents a drone-based camera calibration technique for the calibration of cameras in a broader range of operating environments. The technique is enabled by the use of a drone that is equipped with location sensors. In the proposed approach, the drone is used to sample points in the 3D space and its detection on the images provides the 2D matching points enabling the calibration. To design a flight path that allows for an accurate calibration, the paper proposes a methodology to evaluate the impact of path parameters and drone localization and detection uncertainties on the calibration uncertainty. This methodology is applied to evaluate the performance of different sampling paths for the calibration of a large diversity of cameras for the purpose of recommending reliable path parameters.