• DocumentCode
    2690882
  • Title

    Key frame extraction algorithm for video abstraction applications in underwater videos

  • Author

    Kumar, N. Sathish ; Shobha, G. ; Balaji, S.

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Jain Univ., Ramanagara, India
  • fYear
    2015
  • fDate
    23-25 Feb. 2015
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    It is extremely time consuming for researchers looking for particular events of interest to manually search in the video database. Therefore, there is enormous scope in research in the field of automatic extraction of key frames from underwater video sequences. Analysis of underwater video poses many challenges to existing techniques in computer vision including camera movement, turbidity, uneven background, non uniform lighting, moving objects in the underwater and inaccessibility of environment. The main aim of this paper is to (i) describe about the existing methods for key frame extraction, (ii) emphasize the key challenges in underwater environment, (iii) propose a new method to extract key frames which suits for underwater environment, (iv) perform the automatic detection and characterization of events of interest in underwater videos.
  • Keywords
    computer vision; feature extraction; image sequences; object detection; pose estimation; turbidity; video cameras; video databases; video signal processing; automatic detection; automatic key frame extraction algorithm; camera movement; computer vision; moving object; nonuniform lighting; turbidity; underwater video; underwater video pose analysis; underwater video sequences; uneven background; video abstraction application; video database; Adaptation models; Artificial neural networks; Cameras; Computer vision; Feature extraction; Image color analysis; Lighting; Background Subtraction; PTZ; camera jitter; image registration; video mosaicing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Underwater Technology (UT), 2015 IEEE
  • Conference_Location
    Chennai
  • Print_ISBN
    978-1-4799-8299-8
  • Type

    conf

  • DOI
    10.1109/UT.2015.7108243
  • Filename
    7108243