In this paper, we present a Vision-Based Interface guided by the user gestures. The advantage of our system is that it is built over a motion capture system that recovers the body joints positions of the user’s upper body in real-time. From the computed joints positions we make this data spatially invariant by normalizing limbs positions and sizes, only using the limbs orientations. From limbs orientations, the user posture is represented by an appropriate representation of all the limbs in a histogram. Cumulating the posture histograms we represent a gesture in a temporal invariant form. Finally, using this gesture representation, the performed gestures are classified for generating the desired computer events in real-time. Key words: Vision-Based Gesture Recognition 1 Representation of human postures Previously to recognition, the user’s movements are obtained through a realtime vision-based motion capture system [1]. Using the computed 3D positions of the involved body joints, ...