论文标题
马里奥：用于计算Robocup SPL中视觉统计的模块化和可扩展的体系结构
MARIO: Modular and Extensible Architecture for Computing Visual Statistics in RoboCup SPL
论文作者
论文摘要
该技术报告描述了一个模块化且可扩展的体系结构，用于计算Robocup SPL（Mario）在Robocup 2022的SPL Open Research Challenge中介绍的Robocup SPL（Mario）中的模块化结构，该架构在曼谷（泰国）举行。马里奥（Mario）是一个开源的，可用的软件应用程序，其最终目标是为Robocup SPL社区的发展做出贡献。 Mario附带了一个GUI，该GUI集成了多个机器学习和基于计算机视觉的功能，包括自动摄像机校准，背景减法，同型计算，玩家 +球跟踪和本地化，NAO机器人姿势估计和跌落检测。马里奥（Mario）被排名第一。 1在开放研究挑战中。
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.
