Multi-Domain Referee Dataset: Enabling Recognition of Referee Signals on Robotic Platforms
Abstract
Recognizing referee signals is crucial in human and RoboCup soccer games, where an emphasis currently lies on full robot autonomy through understanding referee signals. To advance towards this goal, we introduce the Multi-Domain Referee Dataset aimed at high-efficiency action recognition in RoboCup and examine the transfer between simulated and real domains in strongly structured settings. Our dataset includes 3,108 action sequences across four domains with over 183,000 images. Utilizing a recognition model on an Intel-Atom-based NAO robot, we demonstrate enhanced performance by merging real and synthetic data, and efficient learning of new signals with synthetic data updates, reducing acquisition efforts for future RoboCup rule modifications. Show more
Publication status
publishedExternal links
Book title
RoboLetics: Workshop on Robot Learning in Athletics @CoRL 2023Publisher
OpenReviewEvent
Subject
Action Recognition; Robotic Soccer; Dataset; Domain AdaptationOrganisational unit
03514 - Van Gool, Luc / Van Gool, Luc
09688 - Yu, Fisher / Yu, Fisher
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