Real-time recognition of human gestures for 3D interaction

A fundamental natural interaction concept is not yet fully exploited in most of the existing human-computer interfaces. Recent technological advances have created the possibility to naturally and significantly enhance the interface perception by means of visual inputs, the so called Vision-Based Interaction (VBI). In this paper, we present a gesture recognition algorithm where the user's movements are obtained through a real-time vision-based motion capture system. Specifically, we focus on recognizing users motions with a particular mean, that is, a gesture. Defining an appropriate representation of the user's motions based on a temporal posture parameterization, we apply non-parametric techniques to learn and recognize the user's gestures in real-time. This scheme of recognition has been tested for controlling a classical computer videogame. The results obtained show an excellent performance in on-line classification and it allows the possibility to achieve a learning phase in real-time due to its computational simplicity.