Adaptive power management of on-chip video memory for multiview video coding

Muhammad Shafique, Bruno Zatt, Fabio Leandro Walter, Sergio Bampi, Jörg Henkel

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

Abstract

An adaptive power management of on-chip video memory for Multiview Video Coding is presented. It leverages texture, motion and disparity properties of objects and their correlations in the 3D-neighborhood. It groups different Macroblocks of a frame and predicts the highly-probable motion/disparity search direction in order to power-gate idle memory regions. Exploited are the statistical properties of Macroblock groups to predict idle sectors. Our approach achieves on average 32% and 61% energy reduction (averaged over various video sequences) compared to state-of-the-art DSW [7] and Level C [12], respectively. The Motion/Disparity Estimation architecture with video memory and power management scheme is implemented using an ASIC flow (IBM-65nm Low-Power technology) and it processes 4-view HD1080p@33fps.

Original languageEnglish (US)
Title of host publicationProceedings of the 49th Annual Design Automation Conference, DAC '12
Pages866-875
Number of pages10
DOIs
StatePublished - 2012
Event49th Annual Design Automation Conference, DAC '12 - San Francisco, CA, United States
Duration: Jun 3 2012Jun 7 2012

Publication series

NameProceedings - Design Automation Conference
ISSN (Print)0738-100X

Other

Other49th Annual Design Automation Conference, DAC '12
CountryUnited States
CitySan Francisco, CA
Period6/3/126/7/12

Keywords

  • adaptivity
  • disparity estimation
  • low-power
  • motion estimation
  • MVC
  • on-chip memory
  • power-gating
  • power-management
  • video coding
  • video memory

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Modeling and Simulation

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