• DocumentCode
    1923595
  • Title

    Media adaptation model based on character object for cognitive TV

  • Author

    Kim, Sungho ; Yong-Ik Yoon

  • Author_Institution
    Dept. of Multimedia Sci., Sookmyung Women´s Univ., Seoul, South Korea
  • fYear
    2013
  • fDate
    28-30 Jan. 2013
  • Firstpage
    487
  • Lastpage
    492
  • Abstract
    Advances in technology for multimedia services have led to a tremendous growth of video contents and accelerated the need to analyze and understand video content. An analysis of sports video, for example, has been a hot research area to identify a number of potential items: player and ball. For the efforts, this paper shows a Cognitive TV framework for the semantic region of interests in sport video service. The framework will issue two contributions in the short classification and object trajectory for the area of sport video. For the contributions, this paper suggests the semantic region of interests (SROI) based on Motion Vector Space (MVF) to analyze sports video. The SROI distinguishes the shot classes that are located in the motion vector space and detects the key objects, like the player and ball in the playing field, using Cognitive lattice algorithm.
  • Keywords
    image classification; image motion analysis; multimedia communication; object detection; sport; television; MVF; SROI; character object trajectory; cognitive TV framework; cognitive lattice algorithm; media adaptation model; motion vector space; multimedia service technology; object detection; semantic region of interest; sport video content service analysis; video acceleration; Cameras; Games; Lattices; Semantics; Support vector machine classification; Trajectory; Vectors; Cognitive Lattice; H.264IMPEG-21SVC; Motion features; Region of Interest; Semantic Shot; Video Classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Networking (ICOIN), 2013 International Conference on
  • Conference_Location
    Bangkok
  • ISSN
    1976-7684
  • Print_ISBN
    978-1-4673-5740-1
  • Electronic_ISBN
    1976-7684
  • Type

    conf

  • DOI
    10.1109/ICOIN.2013.6496428
  • Filename
    6496428