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    Human action recognition in realistic scenes based on Action Bank

    TítuloHuman action recognition in realistic scenes based on Action Bank
    Tipo de publicaciónConference Paper
    Año de publicación2016
    AutoresMartínez, C, Baptista, M, Losada-Gutiérrez, C, Marron, M, Boggian, V
    Idioma de publicaciónEnglish
    Conference NameInternational Work-conference on Bioinformatics and Biomedical Engineering
    Conference LocationGranada
    Fecha de publicación04/2016
    Numero ISBN978-84-16478-75-0
    Palabras claveAction Bank, activity recognition, monoc- ular RGB image processing, video-surveillance

    During the last decades topics such as video analysis and
    image understanding have acquired a big importance due to its inclusion
    in applications such as security, intelligent spaces, assistive living and focused marketing. In order to validate all related works different datasets
    have been distributed within the research community: CAVIAR, KTH,
    Weizmann, INRIA or MuHAVI are some of the most well-known ex-
    amples, but in most cases these datasets have not been created for the
    surveillance application in realistic scenes of interest. Within this context,
    here we present a work that implements a solution for multiple persons'
    action recognition in monocular video sequences, focused on surveillance
    applications. Besides, it is also presented a newly created dataset with
    realistic scenes specifically designed for commercial applications. Development and results of the proposed algorithm and its validation, both
    within well-known datasets as CAVIAR and KTH and within the one
    ad-hoc generated for the applications of interest, are discussed in the

    paperactionbank_iwbbio_final.pdf423.95 KB

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