Research Article

Comparing the streaming of FGS encoded video at different aggregation levels: frame, GoP, and scene

  1. Philippe de Cuetos1,†,
  2. Patrick Seeling2,
  3. Martin Reisslein2,*,
  4. Keith W. Ross3

Article first published online: 15 MAR 2005

DOI: 10.1002/dac.711

Issue

International Journal of Communication Systems

International Journal of Communication Systems

Volume 18, Issue 5, pages 449–464, June 2005

Additional Information

How to Cite

de Cuetos, P., Seeling, P., Reisslein, M. and Ross, K. W. (2005), Comparing the streaming of FGS encoded video at different aggregation levels: frame, GoP, and scene. Int. J. Commun. Syst., 18: 449–464. doi: 10.1002/dac.711

Author Information

  1. 1

    Institut Eurecom, Sophia-Antipolis, France

  2. 2

    Department of Electrical Engineering, Arizona State University, Goldwater Center MC 5706, Tempe AZ 85287-5706, U.S.A.

  3. 3

    Polytechnic University, 6 MetroTech Center, Brooklyn, NY 11201, U.S.A.

  1. †

    He is now with ENST, Paris, France.

*Department of Electrical Engineering, Arizona State University, Goldwater Center MC 5706, Tempe AZ 85287-5706, U.S.A.

Publication History

  1. Issue published online: 27 MAY 2005
  2. Article first published online: 15 MAR 2005
  3. Manuscript Accepted: OCT 2004
  4. Manuscript Revised: SEP 2004
  5. Manuscript Received: MAR 2004

Funded by

  • National Science Foundation. Grant Numbers: Career ANI-0133252, ANI-0136774
  • State of Arizona. Grant Number: IT301
  • Sun Microsystems

SEARCH

SEARCH BY CITATION

ARTICLE TOOLS

Get PDF (283K)

Keywords:

  • fine granularity scalability;
  • multimedia communications;
  • performance evaluation;
  • rate-distortion optimized streaming;
  • scalable video;
  • video scene;
  • video streaming

Abstract

Fine granularity scalability (FGS), a new coding technique that has recently been added to the MPEG-4 video coding standard, allows for the flexible scaling of each individual video frame at very fine granularity. This flexibility makes FGS video very well suited for rate-distortion optimized streaming mechanisms, which minimize the distortion (i.e. maximize the quality) of the streamed video by transmitting the optimal number of bits for each individual frame. The per-frame optimization of the transmission schedule, however, puts a significant computational burden on video servers and intermediate streaming gateways. In this paper we investigate the rate-distortion optimized streaming at different video frame aggregation levels. We find that compared to the optimization for each individual video frame, optimization at the level of video scenes reduces the computational effort dramatically, while reducing the video quality only very slightly. Copyright © 2005 John Wiley & Sons, Ltd.

Get PDF (283K)