Extensions to object recognition in the four-legged league

Authors:
Christopher J. Seysener;Craig L. Murch;Richard H. Middleton
Affiliations:
School of Electrical Engineering & Computer Science, The University of Newcastle, Callaghan, Australia;School of Electrical Engineering & Computer Science, The University of Newcastle, Callaghan, Australia;School of Electrical Engineering & Computer Science, The University of Newcastle, Callaghan, Australia
Venue:
RoboCup 2004
Year:
2005

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Abstract

Humans process images with apparent ease, quickly filtering out useless information and identifying objects based on their shape and colour. However, the undertaking of visual processing and the implementation of object recognition systems on a robot can be a challenging task. While many algorithms exist for machine vision, fewer have been developed with the efficiency required to allow real-time operation on a processor limited platform. This paper focuses on several efficient algorithms designed to identify field landmarks and objects found in the controlled environment of the RoboCup Four-Legged League.