Towards social touch intelligence: developing a robust system for automatic touch recognition

Merel Madeleine Jung

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

    7 Citations (Scopus)
    108 Downloads (Pure)


    Touch behavior is of great importance during social interaction. Automatic recognition of social touch is necessary to transfer the touch modality from interpersonal interaction to other areas such as Human-Robot Interaction (HRI). This paper describes a PhD research program on the automatic detection, classification and interpretation of touch in social interaction between humans and artifacts. Progress thus far includes the recording of a Corpus of Social Touch (CoST) consisting of pressure sensor data of 14 different touch gestures and first classification results. Classification of these 14 gestures resulted in an overall accuracy of 53% using Bayesian classifiers. Further work includes the enhancement of the gesture recognition, building an embodied system for real-time classification and testing this system in a possible application scenario.
    Original languageUndefined
    Title of host publicationProceedings of the 16th International Conference on Multimodal Interaction, ICMI 2014
    Place of PublicationNew York
    PublisherAssociation for Computing Machinery
    Number of pages5
    ISBN (Print)978-1-4503-2885-2
    Publication statusPublished - Nov 2014
    Event16th International Conference on Multimodal Interaction, ICMI 2014 - Istanbul, Turkey, Istanbul, Turkey
    Duration: 12 Nov 201416 Nov 2014
    Conference number: 16

    Publication series



    Conference16th International Conference on Multimodal Interaction, ICMI 2014
    Abbreviated titleICMI
    Other12-16 November 2014


    • EWI-25279
    • Touch gesture recognition
    • Touch sensing
    • METIS-309647
    • Touch corpus
    • IR-93287
    • Human-Robot Interaction (HRI)
    • Social Touch

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