Autonomous color learning on a mobile robot
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
Illumination independent object recognition
RoboCup 2005
Automatic On-Line Color Calibration Using Class-Relative Color Spaces
RoboCup 2007: Robot Soccer World Cup XI
Histogram-Based Visual Object Recognition for the 2007 Four-Legged RoboCup League
SETN '08 Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications
Benchmarks for robotic soccer vision
Robot Soccer World Cup XV
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Color segmentation is typically the first step of vision processing for a robot operating in a color-coded environment, such as RoboCup soccer, and many object recognition modules rely on that.Although many approaches to color segmentation have been proposed, in the official games of the RoboCup Four Legged League manual calibration is still preferred by most of the teams. In this paper we present a method for color segmentation that is based on an adaptive transformation of the color distribution of the image: the transformation is dynamically computed depending on the current image (i.e., it adapts to condition changes) and then it is used for color segmentation with static thresholds. The method requires the setting of only a few parameters and has been proved to be very robust to noise and light variations, allowing for setting parameters only once when arriving at a competition site.The approach has been implemented on AIBO robots, extensively tested in our laboratory, and successfully experimented in the some of the games of the Four Legged League in RoboCup 2005.