• DocumentCode
    432931
  • Title

    Real-time temporal texture characterisation using block-based motion co-occurrence statistics

  • Author

    Rahman, Ashfaqur ; Murshed, Munzitr

  • Author_Institution
    Gippsland Sch. of Comp. & IT, Monash Univ., Churchill, Vic., Australia
  • Volume
    3
  • fYear
    2004
  • fDate
    24-27 Oct. 2004
  • Firstpage
    1593
  • Abstract
    Contemporary temporal texture classification methods use pixel based features thus making the process slow for time sensitive applications like video indexing and surveillance. In this paper, a real-time classification technique is presented by using readily available block based motion vectors. Experimental results demonstrate the ability of the proposed technique to classify a large set of temporal textures in real-time with high accuracy.
  • Keywords
    image classification; image motion analysis; image sequences; image texture; indexing; statistical analysis; surveillance; video signal processing; block-based motion co-occurrence statistics; image sequence; motion vector; real-time temporal texture characterisation; texture classification method; video indexing; video surveillance; Australia; Feature extraction; Fluid flow measurement; Image sequences; Indexing; Motion measurement; Pixel; Spatiotemporal phenomena; Statistical distributions; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2004. ICIP '04. 2004 International Conference on
  • ISSN
    1522-4880
  • Print_ISBN
    0-7803-8554-3
  • Type

    conf

  • DOI
    10.1109/ICIP.2004.1421372
  • Filename
    1421372