Robotics: control, sensing, vision, and intelligence
Robotics: control, sensing, vision, and intelligence
RoboCup-97: Robot Soccer World Cup I
RoboCup-97: Robot Soccer World Cup I
A Segmentation System for Soccer Robot Based on Neural Networks
RoboCup-99: Robot Soccer World Cup III
Camera Calibration Using Rectangular Textures
RobVis '01 Proceedings of the International Workshop on Robot Vision
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This paper describes a practical method for calibrating the geometry and colour information for cameras surveying large rooms. To calibrate the geometry, we use a semi-automatic system to assign real world to pixel coordinates. This information is the input to the Tsai camera calibration method. Our system uses a two stage process in which easily recognizable objects (squares) are used to sort the individual data points and to find missing objects. Fine object features (corners) are used in a second step to determine the object's real world coordinates. An empirical evaluation of the system shows that the average and maximum errors are sufficiently small for our domain. Objects are recognized through coloured spots. The colour calibration uses six thresholds (Three colour ranges (Red, Green, and Blue) and three colour differences (Red - Green, Red - Blue, Green - Blue)). This paper describes a fast threshold comparison routine.