Tracking the activity of participants in a meeting

Hammadi Nait Charif, Stephen J. McKenna

    Research output: Contribution to journalArticlepeer-review

    14 Citations (Scopus)

    Abstract

    A vision system suitable for a smart meeting room able to analyse the activities of its occupants is described. Multiple people were tracked using a particle filter in which samples were iteratively re-weighted using an approximate likelihood in each frame. Trackers were automatically initialised and constrained using simple contextual knowledge of the room layout. Person-person occlusion was handled using multiple cameras. The method was evaluated on video sequences of a six person meeting. The tracker was demonstrated to outperform standard sampling importance re-sampling. All meeting participants were successfully tracked and their actions were recognised throughout the meeting scenarios tested.
    Original languageEnglish
    Pages (from-to)83-93
    Number of pages11
    JournalMachine Vision and Applications
    Volume17
    Issue number2
    DOIs
    Publication statusPublished - 1 May 2006

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