Network-aware video redundancy coding with scene-adaptation for H.263+ video

Jae Young Pyun, Jae Hwan Jeong, Kwang Il Ji, Kyunghun Jang, Sung Jea Ko

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This paper introduces a new error-resilient mechanism based on video redundancy coding (VRC) of H.263 Version 2, formerly known as H.263+. VRC is a mechanism to achieve temporal error resilience in error-prone environments. However, VRC is not suitable for the time-varying error-prone channel. The proposed network-aware VRC mechanism adaptively changes the prediction structure with multiple threads according to the channel status. Also, scene-adaptiveness is incorporated with the network-aware VRC to reduce the motion-jerkiness occurred by an abrupt scene change. Simulation results show that the proposed adaptive VRC mechanism does not only utilize network resources efficiently, but also reduce the fluctuation of the video quality.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsAdnan Yazici, Cevat Sener
PublisherSpringer Verlag
Pages707-714
Number of pages8
ISBN (Print)3540204091, 9783540397373
DOIs
Publication statusPublished - 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2869
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Pyun, J. Y., Jeong, J. H., Ji, K. I., Jang, K., & Ko, S. J. (2003). Network-aware video redundancy coding with scene-adaptation for H.263+ video. In A. Yazici, & C. Sener (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 707-714). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2869). Springer Verlag. https://doi.org/10.1007/978-3-540-39737-3_88