Soccer Player Activity Recognition by a Multivariate Features Integration

Human action recognition is an important research area in the field of computer vision having a great number of real-world applications. This paper presents a multi-view action recognition framework that extracts human silhouette clues from different cameras, analyzes scene dynamics and interprets human behaviors by the integration of multivariate data in fuzzy rule-based system. Different features have been considered for the player action recognition some of them concerning the human silhouette analysis, and some others related to the ball and player kinematics. Experiments were carried out on a multi view image sequences of a public soccer data set.