Analysis of external factors influencing the calibration of binocular cameras

This study utilizes regression analysis to examine the external factors affecting the calibration outcomes of binocular cameras. The experiment employs a binocular camera with fixed focal length and baseline, coupled with a commonly used checkerboard calibration pattern. A series of calibration pattern images were captured and subjected to image processing and parameter computation. Employing factorial experiments, variance analysis was conducted to assess the impact of factors such as black and white spacing between checkerboard patterns, the quantity of calibration images, the number of internal corner points, and the distance between calibration boards on calibration errors. Results indicate that all aforementioned factors influence baseline errors. Findings suggest that optimizing the quantity of calibration images, adjusting black and white spacing in checkerboard patterns, increasing internal corner points, and reducing the distance between calibration boards enhance the precision and performance of binocular cameras in 3D vision applications.