Hand tracking for behaviour understanding

G. McAllister, S. J. McKenna, I. W. Ricketts

    Research output: Contribution to journalArticlepeer-review

    34 Citations (Scopus)


    A real-time computer vision system is described for tracking hands thus enabling behavioural events to be interpreted. Forearms are tracked to provide structural context, enabling mutual occlusion, which occurs when hands cross one another, to be handled robustly. No prior skin colour models are used. Instead adaptive appearance models are learned on-line. A contour distance transform is used to control model adaptation and to fit 2D geometric models robustly. Hands can be tracked whether clothed or unclothed. Results are given for a ‘smart desk’ and an in-vehicle application. The ability to interpret behavioural events of interest when tracking a vehicle driver's hands is described.
    Original languageEnglish
    Pages (from-to)827-840
    Number of pages14
    JournalImage and Vision Computing
    Issue number12
    Publication statusPublished - Oct 2002


    • Hand tracking
    • Gesture recognition
    • Behavioural events
    • Intelligent vehicles
    • Smart desks


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