MARIO: Modular and Extensible Architecture for Computing Visual Statistics in RoboCup SPL
This provides a ready-to-use tool for the RoboCup SPL community, though it is incremental as it builds on existing methods for a specific domain.
The paper tackles the problem of computing visual statistics in RoboCup SPL by introducing MARIO, a modular and extensible architecture that integrates machine learning and computer vision functions, achieving a top ranking in the Open Research Challenge.
This technical report describes a modular and extensible architecture for computing visual statistics in RoboCup SPL (MARIO), presented during the SPL Open Research Challenge at RoboCup 2022, held in Bangkok (Thailand). MARIO is an open-source, ready-to-use software application whose final goal is to contribute to the growth of the RoboCup SPL community. MARIO comes with a GUI that integrates multiple machine learning and computer vision based functions, including automatic camera calibration, background subtraction, homography computation, player + ball tracking and localization, NAO robot pose estimation and fall detection. MARIO has been ranked no. 1 in the Open Research Challenge.