Popularity-aware rate allocation in multi-view video

Attilio Fiandrotti, Jacob Chakareski, Pascal Frossard

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Scopus citations

Abstract

We propose a framework for popularity-driven rate allocation in H.264/MVC-based multi-view video communications when the overall rate and the rate necessary for decoding each view are constrained in the delivery architecture. We formulate a rate allocation optimization problem that takes into account the popularity of each view among the client population and the rate-distortion characteristics of the multi-view sequence so that the performance of the system is maximized in terms of popularity-weighted average quality. We consider the cases where the global bit budget or the decoding rate of each view is constrained. We devise a simple rate-video-quality model that accounts for the characteristics of interview prediction schemes typical of multi-view video. The video quality model is used for solving the rate allocation problem with the help of an interior point optimization method. We then show through experiments that the proposed rate allocation scheme clearly outperforms baseline solutions in terms of popularity-weighted video quality. In particular, we demonstrate that the joint knowledge of the rate-distortion characteristics of the video content, its coding dependencies, and the popularity factor of each view is key in achieving good coding performance in multi-view video systems.

Original languageEnglish (US)
Title of host publicationVisual Communications and Image Processing 2010
DOIs
StatePublished - 2010
Externally publishedYes
EventVisual Communications and Image Processing 2010 - Huangshan, China
Duration: Jul 11 2010Jul 14 2010

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume7744
ISSN (Print)0277-786X

Conference

ConferenceVisual Communications and Image Processing 2010
Country/TerritoryChina
CityHuangshan
Period7/11/107/14/10

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Keywords

  • 3DTV
  • Lagrange optimization
  • Multi-view video
  • Popularity-driven
  • Rate allocation
  • Rate-video-quality modeling

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