A 3d data intensive tele-immersive grid
Proceedings of the international conference on Multimedia
Reducing bandwidth consumption in parallel networked telepresence environments
Proceedings of the 11th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry
A 3D tele-immersion streaming approach using skeleton-based prediction
Proceedings of the 21st ACM international conference on Multimedia
Proceedings of the 10th European Conference on Visual Media Production
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Vision-based full-body 3D reconstruction for tele-immersive applications generates large amount of data points, which have to be sent through the network in real time. In this paper, we introduce a skeleton-based compression method using motion estimation where kinematic parameters of the human body are extracted from the point cloud data in each frame. First we address the issues regarding the data capturing and transfer to a remote site for the tele-immersive collaboration. We compare the results of the existing compression methods and the proposed skeleton-based compression technique. We examine the robustness and efficiency of the algorithm through experimental results with our multi-camera tele-immersion system. The proposed skeleton-based method provides high and flexible compression ratios from 50:1 to 5000:1 with reasonable reconstruction quality (peak signal-to-noise ratio from 28 to 31 dB) while preserving real-time (10+ fps) processing.