Fast Image Segmentation, Object Recognition and Localization in a RoboCup Scenario
RoboCup-99: Robot Soccer World Cup III
A Novel Approach to Efficient Monte-Carlo Localization in RoboCup
RoboCup 2006: Robot Soccer World Cup X
Towards illumination invariance in the legged league
RoboCup 2004
Adaptive Recognition of Color-Coded Objects in Indoor and Outdoor Environments
RoboCup 2007: Robot Soccer World Cup XI
Automatic On-Line Color Calibration Using Class-Relative Color Spaces
RoboCup 2007: Robot Soccer World Cup XI
Gradient vector griding: an approach to shape-based object detection in RoboCup scenarios
Robot Soccer World Cup XV
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Many approaches for object detection based on color coding were published in the RoboCup domain. They are tuned to the typical RoboCup scenario of constant lighting using a static subdivision of the color space. However, such algorithms will soon be of limited use, when playing under changing and finally natural lighting. This paper presents an algorithm for automatic color training, which is able to robustly adapt to different lighting situations online. Using the ACT algorithm a robot is able to play a RoboCup match while the illumination of the field varies.