Sport Field Registration

Sport field registration aims to accurately map the 2D image of a sports field from broadcast video to its 3D real-world coordinates, enabling precise analysis of player movement and ball trajectory. Current research focuses on improving camera calibration techniques, often employing Bayesian frameworks, Kalman filters, or deep learning models (like encoder-decoder networks) to estimate homographies or directly recover camera parameters from field markings and other features. These advancements are crucial for enhancing sports analytics, enabling more accurate performance metrics, and facilitating the development of augmented reality applications for broadcasting and fan engagement.