• DocumentCode
    2298495
  • Title

    A Survey on Video Caption Extraction

  • Author

    Liu, Haibo ; Zhou, Changjian ; Shen, Jing

  • Author_Institution
    Coll. of Comput. Sci. & Technol., Harbin Eng. Univ., Harbin, China
  • fYear
    2010
  • fDate
    1-2 Nov. 2010
  • Firstpage
    43
  • Lastpage
    50
  • Abstract
    Over the last few decades, Content-based image/video retrieval (CBIR/CBVR) problem have developed a new height. As one of the most impartment methods of CBVR, video caption extraction obtained more and more application. A large number of techniques have been proposed to address this problem, we summarized most of the video caption extraction methods, analyzed the advantage and disadvantage of the existed methods. The purpose of this paper is to classify and review these algorithms, discuss benchmark data and performance evaluation, and to point out promising directions for future research.
  • Keywords
    feature extraction; video retrieval; video signal processing; CBIR/CBVR; benchmark data; content based image/video retrieval; performance evaluation; video caption extraction; Feature extraction; Image color analysis; Optical character recognition software; Robustness; Semantics; Streaming media; Support vector machines; caption detection; content-based video retrieval; machine learning; video caption; video caption extraction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Internet Computing for Science and Engineering (ICICSE), 2010 Fifth International Conference on
  • Conference_Location
    Heilongjiang
  • Print_ISBN
    978-1-4244-9954-0
  • Type

    conf

  • DOI
    10.1109/ICICSE.2010.10
  • Filename
    6076539