• DocumentCode
    1999001
  • Title

    Classification of Movies and Television Shows Using Motion

  • Author

    Smith, Mark ; Hashemi, Ray ; Sears, Leslie

  • Author_Institution
    Univ. of Central Arkansas, Conway, AR
  • fYear
    2009
  • fDate
    27-29 April 2009
  • Firstpage
    1056
  • Lastpage
    1060
  • Abstract
    An innovative technique used for categorizing motion pictures and television shows based on motion activity is presented. First, scenes extracted from digitally stored movies and television programs are segmented into separate clips based on various editing effects such as hard cuts, fades and dissolves. Next,the initial frame of the sequence is automatically segmented into meaningful objects using color and texture features using any image segmentation algorithm chosen by the author. An object tracking algorithm utilizing motion is then applied to each Intra (I) frame and each Predicted (P) frame in the video sequence. Interesting objects undergoing the highest degree of motion are then automatically selected for additional analysis. The distance between corresponding objectpsilas centroids existing in adjacent frames is computed for each interesting object. These distances are then used in classifying the clip as being an action or non-action video.
  • Keywords
    entertainment; feature extraction; image classification; image colour analysis; image motion analysis; image segmentation; image texture; video signal processing; color feature; image segmentation; motion activity; movie classification; object tracking algorithm; television show classification; texture feature; Data mining; Image segmentation; Information retrieval; Information technology; Layout; Motion pictures; Multimedia databases; Object segmentation; TV; Video sequences; Video; data mining; objects;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology: New Generations, 2009. ITNG '09. Sixth International Conference on
  • Conference_Location
    Las Vegas, NV
  • Print_ISBN
    978-1-4244-3770-2
  • Electronic_ISBN
    978-0-7695-3596-8
  • Type

    conf

  • DOI
    10.1109/ITNG.2009.250
  • Filename
    5070763