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 language | English |
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Pages (from-to) | 83-93 |
Number of pages | 11 |
Journal | Machine Vision and Applications |
Volume | 17 |
Issue number | 2 |
DOIs | |
Publication status | Published - 1 May 2006 |