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Supervised Video Scene Segmentation using Similarity Measures Supervised Video Scene Segmentation using Similarity Measures

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F13%3APU104500" target="_blank" >RIV/00216305:26220/13:PU104500 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Supervised Video Scene Segmentation using Similarity Measures Supervised Video Scene Segmentation using Similarity Measures

  • Original language description

    Video scene segmentation is a process for dividing video into semantically meaningful blocks. This can help e.g. search engines to divide video into better manageable parts and enable more relevant search in video. Unfortunately, scene segmentation is based on the semantic and therefore it is a difficult task for computers. This work is preliminary study involved into supervised video scene segmentation, which is driven by the way how human segments scenes in a movie. Since these video segments represent semantic parts in video, it can be used for better video annotation and also for searching in videos. As a training set, only high quality movies were used and from these movies 100 training samples have been extracted and used for evaluation. Resulting model is a method based on general color layout, Tamura similarity measure and k-nearest neighbors achieving 97.00% accuracy.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/FR-TI4%2F151" target="_blank" >FR-TI4/151: Research and development of technology for machine emotion detection in unstructured data</a><br>

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2013

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    36th International Conference on Telecommunications and Signal processing

  • ISBN

    978-1-4799-0402-0

  • ISSN

  • e-ISSN

  • Number of pages

    912

  • Pages from-to

    793-797

  • Publisher name

    Neuveden

  • Place of publication

    Neuveden

  • Event location

    Rome

  • Event date

    Jul 2, 2013

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article