Robust multi-view video streaming through adaptive intra refresh video transcoding

A multi-view video (MVV) transcoder has been designed. The objective is to deliver maximum quality 3D video data from the source to the 2D video destination, through a wireless communication channel using all of its available bandwidth. This design makes use of the spatial and view downscaling algorithm. The method involves the reuse of motion information obtained from both the reference frames and views. Consequently, highly compressed MVV is converted into low bit rate single view video that is compliant with H.264/AVC format. Adaptive intra refresh (AIR) error resilience tool is configured to mitigate the error propagation resulting from channel conditions. Experimental results indicate that error resilience plus transcoding performed better than the cascaded technique. Simulation results demonstrated an efficient 3D video streaming service applied to low power mobile devices

Robust Multi-View Video Streaming through Adaptive Intra Refresh Video Transcoding

A multi-view video (MVV) transcoder has been designed. The objective is to deliver maximum quality 3D video data from the source to the 2D video destination, through a wireless communication channel using all of its available bandwidth. This design makes use of the spatial and view downscaling algorithm. The method involves the reuse of motion information obtained from both the reference frames and views. Consequently, highly compressed MVV is converted into low bit rate single view video that is compliant with H.264/AVC format. Adaptive intra refresh (AIR) error resilience tool is configured to mitigate the error propagation resulting from channel conditions. Experimental results indicate that error resilience plus transcoding performed better than the cascaded technique. Simulation results demonstrated an efficient 3D video streaming service applied to low power mobile devices

Multiple Description H.264 Video Coding with Redundant Pictures

Multiple description coding (MDC) o®ers a competitive so- lution for video transmission over lossy packet networks, with a graceful degradation of the reproduced quality as the loss rate increases. This paper illustrates how redundant pictures, an error resilience tool included in H.264/AVC, can be employed in conjunction with multiple state video coding scheme, previously proposed in the literature. The proposed MDC solution is shown to provide superior perfor- mance to state-of-the-art techniques, in terms of improved average luma peak-signal-to-noise-ratio (PSNR), fewer tem- poral °uctuations in the picture quality, and improved ro- bustness to bad estimation of the loss probability in the network

Error resilience video coding in H.264 encoder with potential distortion tracking

In this paper, an efficient rate-distortion (RD) model for H.264 video encoder in packet loss environment is presented. The encoder keeps tracking the potential error propagation on a block basis by taking into account the source characteristics, network conditions as well as the error concealment method. The end-to-end distortion invoked in this RD model is estimated according to the potential error-propagated distortion stored in a distortion map. The distortion map in terms of each frame is derived after the frame is encoded, which can be used for the RDbased encoding of the subsequent frames. Since the channel distortion has been considered in the proposed RD model, the new Lagarangian parameter is derived accordingly. The proposed method outperforms the error robust rate-distortion optimization method in H.264 test model better in terms of both transmission efficiency and computational complexity. 1

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