Color-Calibration of Robot Vision System Using Self-Organizing Feature Maps
ICANN 96 Proceedings of the 1996 International Conference on Artificial Neural Networks
Adaptive Recognition of Color-Coded Objects in Indoor and Outdoor Environments
RoboCup 2007: Robot Soccer World Cup XI
Adaptive supervision of moving objects for mobile robotics applications
Robotics and Autonomous Systems
Gradient vector griding: an approach to shape-based object detection in RoboCup scenarios
Robot Soccer World Cup XV
Benchmarks for robotic soccer vision
Robot Soccer World Cup XV
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This paper presents a method for automatic on-line color calibration of soccer-playing robots. Our method requires a geometrical model of the field-lines in world coordinates, and one of the ball in image coordinates. No specific assumptions are made about the color of the field, ball, or goals except that they are of roughly homogeneous distinct colors, and that the field-lines are bright relative to the field. The classification works by localizing the robot(without using color information), then growing homogeneously colored regions and matching their size and shape with those of the expected regions. If a region matches the expected one, its color is added to the respective color class. This method can be run in a background thread thus enabling the robot to quickly recalibrate in response to changes in illumination.