Feature Extraction Reimagined: Achieving Superior Accuracy in Camera Calibration

Camera calibration is crucial for 3D vision applications. This paper focuses on improving the accuracy of feature extraction, which is a key step in calibration. We address the aliasing problem of star-shaped pattern by introducing a novel dynamic calibration target that synthesizes multiple checkerboard patterns of different angle around pattern center, which significantly improves feature refinement accuracy. Additionally, we propose a novel cost function of feature refinement that accounts for defocus effect, offering a more physically realistic model compared to existing symmetry based method, experiment on a large dataset demonstrate significant improvements in calibration accuracy with reduced computation time. Our code is available from https://github.com/spdfghi/Feature-Extraction-Reimagined-Achieving-Superior-Accuracy-in-Camera-Calibration.git.