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Proceedings Paper

Expanding network video capacity with delay-cognizant video coding
Author(s): Yuan-Chi Chang; David G. Messerschmitt; Thom Carney
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Paper Abstract

Prior work on statistical multiplexing of variable-bit-rate network video shows higher video capacity (more video connections) can be supported if connections have smoother traffic profiles. For delay critical applications like videoconferencing, smoothing a compressed bit stream indiscriminately is not an option because excess delay would be introduced. In this paper, we presented an application of delay cognizant video coding (DCVC) to expand the network video capacity by performing traffic smoothing discriminatively. DCVC segments the raw video data and generates two compressed video flows with differential delay requirements, a delay-critical flow and a delay-relaxed flow. The delay-critical flow carries less video information and is thus less bursty. The delay-relaxed flow complements the first flow and the magnitude of its bursts can be reduced by traffic smoothing. We demonstrated that at equal visual quality measured in PSNR, the network video capacity could be increased by as mush as 50 percent through the two-flow discriminative traffic smoothing.

Paper Details

Date Published: 28 December 1998
PDF: 12 pages
Proc. SPIE 3653, Visual Communications and Image Processing '99, (28 December 1998); doi: 10.1117/12.334730
Show Author Affiliations
Yuan-Chi Chang, Univ. of California/Berkeley (United States)
David G. Messerschmitt, Univ. of California/Berkeley (United States)
Thom Carney, Univ. of California/Berkeley (United States)

Published in SPIE Proceedings Vol. 3653:
Visual Communications and Image Processing '99
Kiyoharu Aizawa; Robert L. Stevenson; Ya-Qin Zhang, Editor(s)

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