Efficient 3D Reconstruction and Streaming for Group-Scale Multi-Client Live Telepresence

PubDate: December 2019

Teams: University of Bonn

Writers: Patrick Stotko; Stefan Krumpen; Michael Weinmann; Reinhard Klein

PDF: Efficient 3D Reconstruction and Streaming for Group-Scale Multi-Client Live Telepresence

Abstract

Sharing live telepresence experiences for teleconferencing or remote collaboration receives increasing interest with the recent progress in capturing and AR/VR technology. Whereas impressive telepresence systems have been proposed on top of on-the-fly scene capture, data transmission and visualization, these systems are restricted to the immersion of single or up to a low number of users into the respective scenarios. In this paper, we direct our attention on immersing significantly larger groups of people into live-captured scenes as required in education, entertainment or collaboration scenarios. For this purpose, rather than abandoning previous approaches, we present a range of optimizations of the involved reconstruction and streaming components that allow the immersion of a group of more than 24 users within the same scene – which is about a factor of 6 higher than in previous work – without introducing further latency or changing the involved consumer hardware setup. We demonstrate that our optimized system is capable of generating high-quality scene reconstructions as well as providing an immersive viewing experience to a large group of people within these live-captured scenes.