Camera Calibration

Camera calibration, the process of determining a camera's intrinsic and extrinsic parameters, is crucial for accurately mapping 3D world points to 2D image pixels. Current research emphasizes developing robust and efficient calibration methods, exploring diverse approaches such as those leveraging novel calibration patterns, collimator systems, and deep learning models (including transformers and Siamese networks) to overcome limitations of traditional techniques. These advancements are vital for improving the accuracy and reliability of numerous computer vision applications, including 3D reconstruction, augmented reality, autonomous driving, and sports analytics.