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  • ICDAR2015 Competition on Video Script Identification (CVSI 2015)

    Author(s)
    Sharma, Nabin
    Mandal, Ranju
    Sharma, Rabi
    Pal, Umapada
    Blumenstein, Michael
    Griffith University Author(s)
    Mandal, Ranju
    Year published
    2015
    Metadata
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    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 ...
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    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.
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    Conference Title
    2015 13TH IAPR INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION (ICDAR)
    DOI
    https://doi.org/10.1109/ICDAR.2015.7333950
    Subject
    Artificial intelligence not elsewhere classified
    Publication URI
    http://hdl.handle.net/10072/340499
    Collection
    • Conference outputs

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