Soccer players recognition by pixels classification in an hybrid color space

Soccer is a very popular sport all over the world. Coaches and sport commentators need accurate informations about soccer games, especially about the players behaviour. These informations can be gathered by inspectors who watch the soccer match and report manually the actions of the players involved in the principal phases of the game. Generally, these inspectors focus their attention on the few players standing near the ball and don't report about the motion of all the other players. So, it seems desirable to design a system which automatically tracks all the players in real-time. That's why, we propose to automatically track each I,layer through the succesive color images of the sequences acquired by a fixed color camera. Each player which is present in the image, is modelized by an active contour model or snake. When, during the soccer match, a player is hidden by another, the snakes which track these two players merge. So, it becomes impossible to track the players, except if the snakes are interactively re-initialized. Fortunately, in most cases, the two players don't belong to the same team. That's why we present an algorithm which recognizes the teams of the players by pixels classification. The learning scheme of the classification process is divided into two steps. The first one deals with the pixels representing the soccer ground which must be withdrawn before considering the players themselves. To eliminate these pixels, the color characteristics of the ground are determined interactively. In a second step, dealing with windows containing only one player of one team, the color features which yield the best discrimination between the two teams are selected. Thanks to these color features, the pixels associated to the players of the two teams form two separated clusters into a color space. In fact, there are many color representation systems and it's interesting to evaluate the features which provide the best separation between the two classes of pixels according to the players soccer suit. Finally, the classification process for image segmentation is based on the three most dicriminating color features which define the coordinates of each pixel in an ''hybride color space''. Thanks to this hybrid color representation, each pixel can be assigned to one of the two classes by a minimum distance classification.