KEYWORDS: Video, Scalable video coding, Distortion, Spatial resolution, Video compression, Temporal resolution, Nickel, Video coding, Signal to noise ratio, Quantization
Wireless video transmission is prone to potentially low data rates and unpredictable degradations due to timevarying
channel conditions. Such degradations are difficult to overcome using conventional video coding techniques.
Scalable video coding offers a flexible bitstream that can be dynamically adapted to fit the prevailing
channel conditions. Advances in scalable video compression techniques, such as the newly adopted scalable
extension of H.264/AVC, as well as recent advances in wireless access technologies offer possibilities for tackling
this challenge. In this paper, a content-aware scheduling and resource allocation scheme is proposed, that uses
a gradient-based scheduling framework in conjunction with scalable video coding techniques to provide multiple
high quality video streams over a range of operating conditions to multiple users. Simulation results show that
the proposed scheme performs better than conventional content-independent scheduling techniques.
The goal of video summarization is to select key frames from a video sequence in order to generate an optimal summary that can accommodate constraints on viewing time, storage, or bandwidth. While video summary generation without transmission considerations has been studied extensively, the problem of rate-distortion
optimized summary generation and transmission in a packet-lossy network has gained little attention. We consider the transmission of summarized video over a packet-lossy network such as the Internet. We depart from traditional rate control methods by not sacrificing the image quality of each transmitted frame but instead focusing on the frames that can be dropped without seriously affecting the quality of the video sequence. We take into account the packet loss probability, and use the end-to-end distortion to optimize the video quality given constraints on the temporal rate of the summary. Different network scenarios such as when a feedback channel is not available, and when a feedback channel is available with the possibility of retransmission, are considered. In each case, we assume a strict end-to-end delay constraint such that the summarized video can be viewed in real-time. We show simulation results for each case, and also discuss the case when the feedback delay may not
be constant.
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