  This paper presents a real-time approach for single-colored ball detection
and tracking. The approach consists of two main phases. In a first offline
calibration phase, the intrinsic parameters of the camera and the radial
distortion are estimated, and a classification of colors is learned from a
sample image of colored balls. The second phase consists of four main steps:
(1) color segmentation of the input image into several regions based on the
offline classification, (2) robust estimation of the circle parameters (3)
refinement of the circle parameters, and (4) ball tracking. The experimental
results showed that the approach presents a good compromise between suitability
for real-time navigation and robustness to occlusions, background congestion
and colors interference in the scene.
