Shape recognition based on a video and multi-sensor system

We present in this paper a real-time system for shape recognition. The proposed system is a video and multi-sensor platform that is able to classify the mobile objects evolving in the scene into several expected categories. The key of the recognition method is to compute mobile object properties thanks to the camera and sensors and then to use Bayesian classifiers. A learning phase based on ground truth data is used to train the Bayesian classifiers. Our recognition method has been integrated into an existing access control device used in public transportation (subway) at RATP (Regie Autonome des Transports Parisiens) to improve safety and comfort, to prevent fraud and to count people for statistical matters. The expected categories in this case are mainly "adult", "child", "suitcase" and "two adults close to each other".