The Visual Computer

, 26:3

Multi-camera tele-immersion system with real-time model driven data compression

A new model-based compression method for massive dynamic point data
Original Article

DOI: 10.1007/s00371-009-0367-8

Cite this article as:
Lien, JM., Kurillo, G. & Bajcsy, R. Vis Comput (2010) 26: 3. doi:10.1007/s00371-009-0367-8

Abstract

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.

Keywords

3D tele-immersion Multi-camera tele-immersion system Point data compression Model-based compression 

Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Jyh-Ming Lien
    • 1
  • Gregorij Kurillo
    • 2
  • Ruzena Bajcsy
    • 2
  1. 1.George Mason UniversityFairfaxUSA
  2. 2.University of CaliforniaBerkeleyUSA

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