An architecture for automatic gesture analysis
AVI '00 Proceedings of the working conference on Advanced visual interfaces
Applications of Support Vector Machines for Pattern Recognition: A Survey
SVM '02 Proceedings of the First International Workshop on Pattern Recognition with Support Vector Machines
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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Support Vector Machines (SVMs) have been recently introduced as techniques for solving pattern recognition and regression estimation problems. SVMs are derived in the framework of statistical learning theory and combine a solid theoretical foundation with very good performances in several applications. In this paper we describe a system able to detect, represent, and recognize visual dynamic events from an image sequence. While the events are initially detected by means of low level visual processing, both the representation and recognition stages are performed with SVMs. Therefore, the system is trained, instead of programmed, to perform the required tasks. The very good results obtained on real image sequences indicate that SVMs can be profitably used for the construction of flexible and effective systems based on computer vision.