• DocumentCode
    1713714
  • Title

    H.264/AVC Intra-only Coding (iAVC) and Neural Network Based Prediction Mode Decision

  • Author

    Yang, Ming ; Bourbakis, Nikolaos

  • Author_Institution
    Dept. of Comput. Sci., Montclair State Univ., Montclair, NJ, USA
  • Volume
    2
  • fYear
    2010
  • Firstpage
    57
  • Lastpage
    60
  • Abstract
    The requirement to transmit video data over unreliable wireless networks is anticipated in the foreseeable future. Significant compression ratio and error resilience are both needed for applications including tele-operated robotics, vehicle-mounted cameras, sensor network, etc. Block-matching based inter-frame coding techniques, such as MPEG-x and H.26x, do not perform well in these scenarios due to error propagation between frames. Intra-only coding technologies, such as Motion-JPEG, exhibit better recovery from network data loss at the price of higher data rates. In order to address these issues, an intra-only coding scheme of H.264/AVC (iAVC) is proposed. In this approach, each frame is coded independently as an I-frame. In order to speed up the coding procedure, we propose a neural network based intra-only prediction mode decision approach, which has the potential to significantly reduce coding complexity. Frame copy is applied to compensate for packet loss. The proposed approach is a good balance between compression performance, memory usage, and error resilience. It achieves compression performance comparable to Motion-JPEG2000, with lower complexity. Low computational complexity and memory usage are very crucial to mobile stations and devices in wireless networks.
  • Keywords
    computational complexity; data compression; error analysis; image matching; neural nets; video coding; H.264 AVC intra-only coding; MPEG-x; block matching based inter frame coding techniques; compression ratio; computational coding complexity reduction; error propagation; error resilience; motion-JPEG2000; neural network based intra only prediction mode decision approach; neural network based prediction mode decision; video data transmission; wireless networks; Artificial neural networks; Automatic voltage control; Complexity theory; Encoding; Image coding; Resilience; Streaming media; H.264/AVC; Motion-JPEG2000; Video; coding; errorresilience; network; wireless;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence (ICTAI), 2010 22nd IEEE International Conference on
  • Conference_Location
    Arras
  • ISSN
    1082-3409
  • Print_ISBN
    978-1-4244-8817-9
  • Type

    conf

  • DOI
    10.1109/ICTAI.2010.84
  • Filename
    5671429