Accurate and efficient geometric calibration is important to precisely acquire geometric information in thermal cameras. Typically, the calibration procedure involves obtaining defined control points from the images of a calibration target and utilizing them to estimate the geometric calibration parameters based on a camera model. Calibration targets include checkerboards, circle grids, Hermann grids, and specially designed patterns. Thermal cameras typically have lower resolution than visible cameras and the control points are localized by creating contrast through heating. These differences make the calibration process of thermal cameras more complex. Conventional thermal camera calibration methods require that the entire calibration target is captured and that all the control points from each image are identified. Due to these limitations, geometric calibration of a thermal camera traditionally requires advanced image processing or substantial manual intervention.This work presents a calibration method using a ChArUco board as the calibration target. The proposed method allows the calibration to be performed with partial-view images and does not require that all the control points from each image are extracted, thereby allowing the calibration to be performed without requiring complex image processing. The proposed calibration method was successfully implemented to estimate the calibration parameters of two different thermal cameras; in both cases achieving an overall mean reprojection error below 0.4 pixels. The effectiveness of the approach was further demonstrated by performing the calibration with a lower mean reprojection error than the MATLAB camera calibrator app. Furthermore, the effectiveness of using different heat sources to create contrast was evaluated.
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