• DocumentCode
    671381
  • Title

    A semi-parametric approach for football video annotation

  • Author

    Mentzelopoulos, Markos ; Psarrou, Alexandra ; Angelopoulou, A. ; Garcia-Rodriguez, Jose

  • Author_Institution
    Dept. of Comput. Sci. & Software Eng., Univ. of Westminster, London, UK
  • fYear
    2013
  • fDate
    4-9 Aug. 2013
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    Automatic sports video segmentation is a fast growth area of research in the visual information retrieval field. This paper presents a semi-parametric algorithm for parsing football video structures. The approach works on a two interleaved based process that closely collaborate towards a common goal. The core part of the proposed method focus performs a fast automatic football video annotation by looking at the enhance entropy variance within a series of shot frames. The entropy is extracted on the Hue parameter from the HSV color system, not as a global feature but in spatial domain to identify regions within a shot that will characterize a certain activity within the shot period. The second part of the algorithm works towards the identification of dominant color regions that could represent players and playfield for further activity recognition. Experimental results shows that the proposed football video segmentation algorithm performs with high accuracy.
  • Keywords
    entropy; image colour analysis; image segmentation; sport; video signal processing; HSV color system; Hue parameter; automatic sports video segmentation; entropy extracted; fast automatic football video annotation; football video structure parsing; semiparametric approach; Clustering algorithms; Entropy; Feature extraction; Histograms; Image color analysis; Semantics; Video sequences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2013 International Joint Conference on
  • Conference_Location
    Dallas, TX
  • ISSN
    2161-4393
  • Print_ISBN
    978-1-4673-6128-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.2013.6706720
  • Filename
    6706720