A 3D tele-immersion streaming approach using skeleton-based prediction

Abstract

3D collaborative Tele-Immersive environments allow reconstruction of real world 3D scenes in the virtual world across multiple physical locations. This kind of reconstruction results in a lot of 3D data being transmitted over the internet in real time. The current systems allow for transmission at low frame rates due to the large volume of data and network bandwidth restrictions. In this paper we propose a prediction based approach that generates future frames by animating the live model based on few skeleton points. By doing so the magnitude of data transmitted is reduced to few hundred bytes. The prediction errors are corrected when an entire frame is received. This approach allows minimal amounts (few bytes) of data to be transmitted per frame, thus allowing for high frame rates and still maintain an acceptable visual quality of reconstruction at the receiver side.