• DocumentCode
    3695280
  • Title

    ICDAR2015 Competition on Video Script Identification (CVSI 2015)

  • Author

    Nabin Sharma;Ranju Mandal;Rabi Sharma;Umapada Pal;Michael Blumenstein

  • Author_Institution
    School of Information and Communication Technology, Griffith University, Queensland, Australia
  • fYear
    2015
  • Firstpage
    1196
  • Lastpage
    1200
  • Abstract
    This paper presents the final results of the ICDAR 2015 Competition on Video Script Identification. A description and performance of the participating systems in the competition are reported. The general objective of the competition is to evaluate and benchmark the available methods on word-wise video script identification. It also provides a platform for researchers around the globe to particularly address the video script identification problem and video text recognition in general. The competition was organised around four different tasks involving various combinations of scripts comprising tri-script and multi-script scenarios. The dataset used in the competition comprised ten different scripts. In total, six systems were received from five participants over the tasks offered. This report details the competition dataset specifications, evaluation criteria, summary of the participating systems and their performance across different tasks. The systems submitted by Google Inc. were the winner of the competition for all the tasks, whereas the systems received from Huazhong University of Science and Technology (HUST) and Computer Vision Center (CVC) were very close competitors.
  • Keywords
    Google
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition (ICDAR), 2015 13th International Conference on
  • Type

    conf

  • DOI
    10.1109/ICDAR.2015.7333950
  • Filename
    7333950