Worcester Polytechnic Institute Electronic Theses and Dissertations Collection

Title page for ETD etd-102408-150542


Document Typedissertation
Author Namewang, yubing
Email Address wang_yubing at emc.com
URNetd-102408-150542
TitleModeling and Evaluating Feedback-Based Error Control for Video Transfer
DegreePhD
DepartmentComputer Science
Advisors
  • Mark Claypool, Advisor
  • Robert Kinicki, Co-Advisor
  • Dan Dougherty, Committee Member
  • Ketan Mayer-Patel, Committee Member
  • Keywords
  • H.264
  • PSNR
  • Error Control
  • RPS
  • Retransmission
  • VQM
  • Date of Presentation/Defense2008-08-27
    Availability unrestricted

    Abstract

    Packet loss can be detrimental to real-time interactive video over lossy networks because one lost video packet can propagate errors to many subsequent video frames due to the encoding dependency between frames. Feedback-based error control techniques use feedback information from the decoder to adjust coding parameters at the encoder or retransmit lost packets to reduce the error propagation due to data loss. Feedback-based error control techniques have been shown to be more effective than trying to conceal the error at the encoder or decoder alone since they allow the encoder and decoder to cooperate in the error control process. However, there has been no systematic exploration of the impact of video content and network conditions on the performance of feedback-based error control techniques. In particular, the impact of packet loss, round-trip delay, network capacity constraint, video motion and reference distance on the quality of videos using feedback-based error control techniques have not been systematically studied.

    This thesis presents analytical models for the major feedback-based error control techniques: Retransmission, Reference Picture Selection (both NACK and ACK modes) and Intra Update. These feedback-based error control techniques have been included in H.263/H.264 and MPEG4, the state of the art video in compression standards. Given a round-trip time, packet loss rate, network capacity constraint, our models can predict the quality for a streaming video with retransmission, Intra Update and RPS over a lossy network. In order to exploit our analytical models, a series of studies has been conducted to explore the effect of reference distance, capacity constraint and Intra coding on video quality. The accuracy of our analytical models in predicting the video quality under different network conditions is validated through simulations. These models are used to examine the behavior of feedback-based error control schemes under a variety of network conditions and video content through a series of analytic experiments.

    Analysis shows that the performance of feedback-based error control techniques is affected by a variety of factors including round-trip time, loss rate, video content and the Group of Pictures (GOP) length. In particular: 1) RPS NACK achieves the best performance when loss rate is low while RPS ACK outperforms other repair techniques when loss rate is high. However RPS ACK performs the worst when loss rate is low. Retransmission performs the worst when the loss rate is high; 2) for a given round-trip time, the loss rate where RPS NACK performs worse than RPS ACK is higher for low motion videos than it is for high motion videos; 3) Videos with RPS NACK always perform the same or better than videos without repair. However, when small GOP sizes are used, videos without repair perform better than videos with RPS ACK; 4) RPS NACK outperform Intra Update for low-motion videos. However, the performance gap between RPS NACK and Intra Update drops when the round-trip time or the intensity of video motion increases. 5) Although the above trends hold for both VQM and PSNR, when VQM is the video quality metric the performance results are much more sensitive to network loss. 6) Retransmission is effective only when the round-trip time is low. When the round-trip time is high, Partial Retransmission achieves almost the same performance as Full Retransmission. These insights derived from our models can help determine appropriate choices for feedback-based error control techniques under various network conditions and video content.

    Files
  • Thesis_v6.pdf

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