• DocumentCode
    3349777
  • Title

    Distortion chains for predicting the video distortion for general packet loss patterns

  • Author

    Chakareski, Jacob ; Apostolopoulos, John ; Tan, Wai-tian ; Wee, Susie ; Girod, Bernd

  • Author_Institution
    Streaming Media Syst. Group, Hewlett Packard Labs., Palo Alto, CA, USA
  • Volume
    5
  • fYear
    2004
  • fDate
    17-21 May 2004
  • Abstract
    When designing a system for video communication over a lossy packet network, it is highly beneficial to have a mechanism for accurately predicting the mean-squared error (MSE) distortion that results from different packet loss patterns. The paper proposes a distortion chains model for accurately predicting the end-to-end distortion for different general packet loss patterns. The performance is examined using JVT/H.264 encoded video sequences and previous frame error concealment. It is shown that, for all tested sequences, the proposed model predicts the total distortion due to a packet loss pattern within a 10% error bound 80% of the time, as compared to the conventional additive approach which achieves the same accuracy less then 40% of the time.
  • Keywords
    distortion; error correction; image sequences; mean square error methods; prediction theory; telecommunication networks; video coding; visual communication; JVT/H.264 encoded video sequences; MSE distortion; distortion chains model; lossy packet network; mean-squared error distortion; packet loss patterns; previous frame error concealment; video communication; video distortion prediction; Bit rate; Communication switching; Information systems; Jacobian matrices; Laboratories; Packet switching; Predictive models; Streaming media; Testing; Video sequences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-8484-9
  • Type

    conf

  • DOI
    10.1109/ICASSP.2004.1327282
  • Filename
    1327282