Self-Stimulatory Behaviours in the Wild for Autism Diagnosis

Shyam RAJAGOPALAN, Abhinav Dhall, Roland GOECKE

    Research output: A Conference proceeding or a Chapter in BookConference contribution

    9 Citations (Scopus)

    Abstract

    Autism Spectrum Disorders (ASD), often referred to as autism, are neurological disorders characterised by deficits in cognitive skills, social and communicative behaviours. A common way of diagnosing ASD is by studying behavioural cues expressed by the children. We introduce a new publicly-available dataset of children videos exhibiting self-stimulatory (stimming) behaviours commonly used for autism diagnosis. These videos, posted by parents/caregivers in public domain websites, are collected and annotated for the stimming behaviours. These videos are extremely challenging for automatic behaviour analysis as they are recorded in uncontrolled natural settings. The dataset contains 75 videos with an average duration of 90 seconds per video, grouped under three categories of stimming behaviours: arm flapping, head banging and spinning. We also provide baseline results of tests conducted on this dataset using a standard bag of words approach for human action recognition. To the best of our knowledge, this is the first attempt in publicly making available a Self-Stimulatory Behaviour Dataset (SSBD) of children videos recorded in natural settings
    Original languageEnglish
    Title of host publicationProceedings of the IEEE International Conference on Computer Vison Workshops (ICCV2013)
    EditorsDavid Forsyth, Yin Li, James M Rehg
    Place of PublicationPiscataway, USA
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    Pages755-761
    Number of pages7
    ISBN (Print)9781479930227
    DOIs
    Publication statusPublished - 2013
    Event2013 IEEE International conference on computer vision workshops - Sydney, Sydney, Australia
    Duration: 2 Dec 20138 Dec 2013

    Workshop

    Workshop2013 IEEE International conference on computer vision workshops
    CountryAustralia
    CitySydney
    Period2/12/138/12/13

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    Cite this

    RAJAGOPALAN, S., Dhall, A., & GOECKE, R. (2013). Self-Stimulatory Behaviours in the Wild for Autism Diagnosis. In D. Forsyth, Y. Li, & J. M. Rehg (Eds.), Proceedings of the IEEE International Conference on Computer Vison Workshops (ICCV2013) (pp. 755-761). Piscataway, USA: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICCVW.2013.103
    RAJAGOPALAN, Shyam ; Dhall, Abhinav ; GOECKE, Roland. / Self-Stimulatory Behaviours in the Wild for Autism Diagnosis. Proceedings of the IEEE International Conference on Computer Vison Workshops (ICCV2013). editor / David Forsyth ; Yin Li ; James M Rehg. Piscataway, USA : IEEE, Institute of Electrical and Electronics Engineers, 2013. pp. 755-761
    @inproceedings{8d71fe7eb487498d840b185661f13620,
    title = "Self-Stimulatory Behaviours in the Wild for Autism Diagnosis",
    abstract = "Autism Spectrum Disorders (ASD), often referred to as autism, are neurological disorders characterised by deficits in cognitive skills, social and communicative behaviours. A common way of diagnosing ASD is by studying behavioural cues expressed by the children. We introduce a new publicly-available dataset of children videos exhibiting self-stimulatory (stimming) behaviours commonly used for autism diagnosis. These videos, posted by parents/caregivers in public domain websites, are collected and annotated for the stimming behaviours. These videos are extremely challenging for automatic behaviour analysis as they are recorded in uncontrolled natural settings. The dataset contains 75 videos with an average duration of 90 seconds per video, grouped under three categories of stimming behaviours: arm flapping, head banging and spinning. We also provide baseline results of tests conducted on this dataset using a standard bag of words approach for human action recognition. To the best of our knowledge, this is the first attempt in publicly making available a Self-Stimulatory Behaviour Dataset (SSBD) of children videos recorded in natural settings",
    keywords = "Computational behaviour analysis, Self-stimulatory behaviours, Autism",
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    RAJAGOPALAN, S, Dhall, A & GOECKE, R 2013, Self-Stimulatory Behaviours in the Wild for Autism Diagnosis. in D Forsyth, Y Li & JM Rehg (eds), Proceedings of the IEEE International Conference on Computer Vison Workshops (ICCV2013). IEEE, Institute of Electrical and Electronics Engineers, Piscataway, USA, pp. 755-761, 2013 IEEE International conference on computer vision workshops, Sydney, Australia, 2/12/13. https://doi.org/10.1109/ICCVW.2013.103

    Self-Stimulatory Behaviours in the Wild for Autism Diagnosis. / RAJAGOPALAN, Shyam; Dhall, Abhinav; GOECKE, Roland.

    Proceedings of the IEEE International Conference on Computer Vison Workshops (ICCV2013). ed. / David Forsyth; Yin Li; James M Rehg. Piscataway, USA : IEEE, Institute of Electrical and Electronics Engineers, 2013. p. 755-761.

    Research output: A Conference proceeding or a Chapter in BookConference contribution

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    AB - Autism Spectrum Disorders (ASD), often referred to as autism, are neurological disorders characterised by deficits in cognitive skills, social and communicative behaviours. A common way of diagnosing ASD is by studying behavioural cues expressed by the children. We introduce a new publicly-available dataset of children videos exhibiting self-stimulatory (stimming) behaviours commonly used for autism diagnosis. These videos, posted by parents/caregivers in public domain websites, are collected and annotated for the stimming behaviours. These videos are extremely challenging for automatic behaviour analysis as they are recorded in uncontrolled natural settings. The dataset contains 75 videos with an average duration of 90 seconds per video, grouped under three categories of stimming behaviours: arm flapping, head banging and spinning. We also provide baseline results of tests conducted on this dataset using a standard bag of words approach for human action recognition. To the best of our knowledge, this is the first attempt in publicly making available a Self-Stimulatory Behaviour Dataset (SSBD) of children videos recorded in natural settings

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    RAJAGOPALAN S, Dhall A, GOECKE R. Self-Stimulatory Behaviours in the Wild for Autism Diagnosis. In Forsyth D, Li Y, Rehg JM, editors, Proceedings of the IEEE International Conference on Computer Vison Workshops (ICCV2013). Piscataway, USA: IEEE, Institute of Electrical and Electronics Engineers. 2013. p. 755-761 https://doi.org/10.1109/ICCVW.2013.103