Skeleton-Based Data Compression for Multi-camera Tele-Immersion System

  • Jyh-Ming Lien
  • Gregorij Kurillo
  • Ruzena Bajcsy
Conference paper

DOI: 10.1007/978-3-540-76858-6_69

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4841)
Cite this paper as:
Lien JM., Kurillo G., Bajcsy R. (2007) Skeleton-Based Data Compression for Multi-camera Tele-Immersion System. In: Bebis G. et al. (eds) Advances in Visual Computing. ISVC 2007. Lecture Notes in Computer Science, vol 4841. Springer, Berlin, Heidelberg

Abstract

Image-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 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).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Jyh-Ming Lien
    • 1
  • Gregorij Kurillo
    • 2
  • Ruzena Bajcsy
    • 2
  1. 1.George Mason University, Fairfax, VA 
  2. 2.University of California, Berkeley, CA 

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