首页 /研究 /MARIO: Modular and Extensible Architecture for Computing Visual Statistics in RoboCup SPL
PERCEPTION

MARIO: Modular and Extensible Architecture for Computing Visual Statistics in RoboCup SPL

Domenico D. Bloisi, Andrea Pennisi, Cristian Zampino, Flavio Biancospino, Francesco Laus, Gianluca Di Stefano, Michele Brienza, Rocchina Romano

发表年份
2022
引用次数
2
访问权限
开放获取

摘要

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.

关键词

Computer scienceModular designArtificial intelligenceArchitectureRobotRoboticsSoftwareOpen sourceBackground subtractionComputational statistics

相关论文

查看 PERCEPTION 分类全部论文