Toward natural interaction through visual recognition of body gestures in real-time

In most of the existing human–computer interfaces, enactive knowledge as new natural interaction paradigm has not been fully exploited yet. Recent technological advances have created the possibility to enhance naturally and significantly the interface perception by means of visual inputs, the so-called Vision-Based Interfaces (VBI). In the present paper, we explore the recovery of the user’s body posture by means of combining robust computer vision techniques and a well known inverse kinematics algorithm in real-time. Specifically, we focus on recognizing the user’s motions with a particular mean, that is, a body gesture. Defining an appropriate representation of the user’s body posture based on a temporal parameterization, we apply non-parametric techniques to learn and recognize the user’s body gestures. This scheme of recognition has been applied to control a computer videogame in real-time to show the viability of the presented approach.