Tracking the activity of participants in a meeting.

This source preferred by Hammadi Nait-Charif

Authors: McKenna, S.J. and Nait-Charif, H.

http://www.springerlink.com/content/qtr66278880k6512/

Journal: Machine Vision and Applications

Volume: 17

Pages: 83-93

ISSN: 0932-8092

DOI: 10.1007/s00138-006-0015-5

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.

This data was imported from DBLP:

Authors: Nait-Charif, H. and McKenna, S.J.

Journal: Mach. Vis. Appl.

Volume: 17

Pages: 83-93

The data on this page was last updated at 05:12 on February 21, 2020.