Correlation estimation with particle-based belief propagation for distributed video coding

L. Stankovic, V. Stankovic, S. Wang, S. Cheng

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

6 Citations (Scopus)

Abstract

In this paper, we propose an adaptive Distributed Video Coding (DVC) scheme that dynamically estimates correlation statistics of the scene in a video sequence to enhance belief-propagation (BP) Slepian-Wolf (SW) decoding. In order to exploit the robustness of distributed source coding (DSC) designs, we integrate particle filtering with standard BP decoding in one factor graph to estimate online correlation among source and side information. Our proposed system boasts improved performance over classical DVC without correlation estimation, due to improved knowledge of correlation statistics via the combination of bit-plane coding and particle-based BP tracking in each frame, as shown by our results.

Original languageEnglish
Title of host publication2011 IEEE international conference on acoustics, speech and signal processing
Place of PublicationNew York
PublisherIEEE
Pages1505-1508
Number of pages4
ISBN (Print)9781457705397
DOIs
Publication statusPublished - 2011
EventIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) - Prague, Czech Republic
Duration: 22 May 201127 May 2011

Publication series

NameInternational Conference on Acoustics Speech and Signal Processing ICASSP
PublisherIEEE
ISSN (Print)1520-6149

Conference

ConferenceIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
CountryCzech Republic
CityPrague
Period22/05/1127/05/11

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Keywords

  • correlation estimation
  • side-information
  • distributed source
  • belief-propagation
  • particle filtering
  • video coding

Cite this

Stankovic, L., Stankovic, V., Wang, S., & Cheng, S. (2011). Correlation estimation with particle-based belief propagation for distributed video coding. In 2011 IEEE international conference on acoustics, speech and signal processing (pp. 1505-1508). (International Conference on Acoustics Speech and Signal Processing ICASSP ). New York: IEEE. https://doi.org/10.1109/ICASSP.2011.5946779