Ball 3D Localization

Ball 3D localization aims to accurately determine the three-dimensional position of a ball in real-time, a crucial task for applications ranging from sports analytics to robotics. Current research focuses on developing robust methods using single or multiple calibrated cameras, often incorporating deep learning models like convolutional neural networks to estimate ball size and position from image data, sometimes augmented by information such as human pose or environmental context. These advancements improve accuracy and efficiency compared to traditional approaches, enabling more precise trajectory prediction and enhanced understanding of ball motion in dynamic environments. The resulting improvements have significant implications for sports analysis, autonomous systems, and human-computer interaction.