• DocumentCode
    1683661
  • Title

    Fast Compressed Domain Motion Detection in H.264 Video Streams for Video Surveillance Applications

  • Author

    Szczerba, Krzysztof ; Forchhammer, SØren ; StØttrup-Andersen, Jesper ; Eybye, Peder Tanderup

  • Author_Institution
    DTU Fotonik, Tech. Univ. of Denmark, Lyngby, Denmark
  • fYear
    2009
  • Firstpage
    478
  • Lastpage
    483
  • Abstract
    This paper presents a novel approach to fast motion detection in H.264/MPEG-4 advanced video coding (AVC) compressed video streams for IP video surveillance systems. The goal is to develop algorithms which may be useful in a real-life industrial perspective by facilitating the processing of large numbers of video streams on a single server. The focus of the work is on using the information in coded video streams to reduce the computational complexity and memory requirements, which translates into reduced hardware requirements and costs. The devised algorithm detects and segments activity based on motion vectors embedded in the video stream without requiring a full decoding and reconstruction of video frames. To improve the robustness to noise, a confidence measure based on temporal and spatial clues is introduced to increase the probability of correct detection. The algorithm was tested on indoor surveillance H.264 sequences.
  • Keywords
    IP networks; motion compensation; video coding; video streaming; video surveillance; H.264; IP video surveillance systems; MPEG-4; advanced video coding; motion detection; video streams; Automatic voltage control; Computational complexity; Costs; Hardware; MPEG 4 Standard; Motion detection; Streaming media; Video coding; Video compression; Video surveillance; H.264; compressed domain; motion detection; surveillance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Video and Signal Based Surveillance, 2009. AVSS '09. Sixth IEEE International Conference on
  • Conference_Location
    Genova
  • Print_ISBN
    978-1-4244-4755-8
  • Electronic_ISBN
    978-0-7695-3718-4
  • Type

    conf

  • DOI
    10.1109/AVSS.2009.78
  • Filename
    5279618