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, 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

Error resilience and concealment techniques for high-efficiency video coding

This thesis investigates the problem of robust coding and error concealment in High Efficiency Video Coding (HEVC). After a review of the current state of the art, a simulation study about error robustness, revealed that the HEVC has weak protection against network losses with significant impact on video quality degradation. Based on this evidence, the first contribution of this work is a new method to reduce the temporal dependencies between motion vectors, by improving the decoded video quality without compromising the compression efficiency. The second contribution of this thesis is a two-stage approach for reducing the mismatch of temporal predictions in case of video streams received with errors or lost data. At the encoding stage, the reference pictures are dynamically distributed based on a constrained Lagrangian rate-distortion optimization to reduce the number of predictions from a single reference. At the streaming stage, a prioritization algorithm, based on spatial dependencies, selects a reduced set of motion vectors to be transmitted, as side information, to reduce mismatched motion predictions at the decoder. The problem of error concealment-aware video coding is also investigated to enhance the overall error robustness. A new approach based on scalable coding and optimally error concealment selection is proposed, where the optimal error concealment modes are found by simulating transmission losses, followed by a saliency-weighted optimisation. Moreover, recovery residual information is encoded using a rate-controlled enhancement layer. Both are transmitted to the decoder to be used in case of data loss. Finally, an adaptive error resilience scheme is proposed to dynamically predict the video stream that achieves the highest decoded quality for a particular loss case. A neural network selects among the various video streams, encoded with different levels of compression efficiency and error protection, based on information from the video signal, the coded stream and the transmission network. Overall, the new robust video coding methods investigated in this thesis yield consistent quality gains in comparison with other existing methods and also the ones implemented in the HEVC reference software. Furthermore, the trade-off between coding efficiency and error robustness is also better in the proposed methods

Video over DSL with LDGM Codes for Interactive Applications

Digital Subscriber Line (DSL) network access is subject to error bursts, which, for interactive video, can introduce unacceptable latencies if video packets need to be re-sent. If the video packets are protected against errors with Forward Error Correction (FEC), calculation of the application-layer channel codes themselves may also introduce additional latency. This paper proposes Low-Density Generator Matrix (LDGM) codes rather than other popular codes because they are more suitable for interactive video streaming, not only for their computational simplicity but also for their licensing advantage. The paper demonstrates that a reduction of up to 4 dB in video distortion is achievable with LDGM Application Layer (AL) FEC. In addition, an extension to the LDGM scheme is demonstrated, which works by rearranging the columns of the parity check matrix so as to make it even more resilient to burst errors. Telemedicine and video conferencing are typical target applications