On the accuracy and complexity of rate-distortion models for fine-grained scalable video sequences
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Optimal multilayer adaptation of SVC video over heterogeneous environments
Advances in Multimedia
H.264/AVC baseline profile decoder complexity analysis
IEEE Transactions on Circuits and Systems for Video Technology
Optimized Rate-Distortion Extraction With Quality Layers in the Scalable Extension of H.264/AVC
IEEE Transactions on Circuits and Systems for Video Technology
Overview of the Scalable Video Coding Extension of the H.264/AVC Standard
IEEE Transactions on Circuits and Systems for Video Technology
Scalable video transmission: packet loss induced distortion modeling and estimation
Proceedings of the 21st international workshop on Network and operating systems support for digital audio and video
A game theoretic approach to video streaming over peer-to-peer networks
Image Communication
Adaptation strategies for MGS scalable video streaming
Image Communication
Efficient bitstream extraction for scalable video based on simulated annealing
Concurrency and Computation: Practice & Experience
Power consumption analysis of constant bit rate video transmission over 3G networks
Computer Communications
A fast algorithm of bitstream extraction using distortion prediction based on simulated annealing
Journal of Visual Communication and Image Representation
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The newly adopted scalable extension of H.264/AVC video coding standard (SVC) demonstrates significant improvements in coding efficiency in addition to an increased degree of supported scalability relative to the scalable profiles of prior video coding standards. Due to the complicated hierarchical prediction structure of the SVC and the concept of key pictures, content-aware rate adaptation of SVC bit streams to intermediate bit rates is a nontrivial task. The concept of quality layers has been introduced in the design of the SVC to allow for fast content-aware prioritized rate adaptation. However, existing quality layer assignment methods are suboptimal and do not consider all network abstraction layer (NAL) units from different layers for the optimization. In this paper, we first propose a technique to accurately and efficiently estimate the quality degradation resulting from discarding an arbitrary number of NAL units from multiple layers of a bitstream by properly taking drift into account. Then, we utilize this distortion estimation technique to assign quality layers to NAL units for a more efficient extraction. Experimental results show that a significant gain can be achieved by the proposed scheme.