Modeling and Evaluating Feedback-Based Error Control for Video Transfer

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, roundtrip 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