What motion patterns tell us about soccer teams

Abstract

A qualitative representation of motion patterns is presented that forms an interface between low-level concepts of behaviours and high-level concepts of reasoning. How the patterns can be employed for characterising interaction patterns in soccer is demonstrated using the simulation league; also, specific soccer scenes from real games prove their adequacy. The advantages of our approach are: it supports the limited abilities of robots in the different RoboCup leagues, i. e. it relies on coarse positional distinctions that are reliably obtainable and easily translated into action; the analysis is directly derived from raw data without the need for any preprocessing steps; both situations can be dealt with, egocentric viewpoints of individuals and the bird's eye view; the approach is independent on the domain, i. e. generalises to arbitrary spatiotemporal interaction patterns. © 2009 Springer Berlin Heidelberg.