Multimedia implicit tagging using EEG signals

M. Soleymani, Maja Pantic

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    28 Citations (Scopus)
    127 Downloads (Pure)


    Electroencephalogram (EEG) signals reflect brain activities associated with emotional and cognitive processes. In this paper, we demonstrate how they can be used to find tags for multimedia content without users' direct input. Alternative methods for multimedia tagging is attracting increasing interest from multimedia community. The new portable EEG helmets are paving the way for employing brain waves in human computer interaction. In this paper, we demonstrate the performance of EEG for tagging purposes using two different scenarios on MAHNOB-HCI database. First, an emotional tagging and classification using a reduced set of electrodes is presented. The emotional responses of 24 participants to short video clips are classified into three classes on arousal and valence. We show how a reduced set of electrodes based on previous studies can preserve and even enhance the emotional classification rate. We then demonstrate the feasibility of using EEG signals for tag relevance tasks. A set of images were shown to participants first, without any tag and then with a relevant or irrelevant tag. The relevance of the tag was assessed based on the EEG responses of the participants in the first second after the tag was depicted. Finally, we demonstrate that by aggregating multiple participants' responses we can significantly improve the tagging accuracy.
    Original languageEnglish
    Title of host publicationProceedings of the IEEE International Conference on Multimedia and Expo, ICME 2013
    Place of PublicationUSA
    Number of pages6
    ISBN (Print)978-1-4799-0015-2
    Publication statusPublished - Jul 2013
    EventIEEE International Conference on Multimedia and Expo, ICME 2013 - San Jose, United States
    Duration: 15 Jul 201319 Jul 2013

    Publication series

    PublisherIEEE Computer Society
    ISSN (Print)1945-7871


    ConferenceIEEE International Conference on Multimedia and Expo, ICME 2013
    Abbreviated titleICME
    Country/TerritoryUnited States
    CitySan Jose


    • EWI-24326
    • HMI-HF: Human Factors
    • EEG
    • tag relevance
    • IR-89321
    • Implicit Tagging
    • Multi-media
    • METIS-302653
    • Affect


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