Tracking the activity of participants in a meeting

TY - JOUR

T1 - Tracking the activity of participants in a meeting

AU - Charif, Hammadi Nait

AU - McKenna, Stephen J.

N1 - Copyright 2011 Elsevier B.V., All rights reserved.

PY - 2006/5/1

Y1 - 2006/5/1

N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/33645669920

U2 - 10.1007/s00138-006-0015-5

DO - 10.1007/s00138-006-0015-5

M3 - Article

AN - SCOPUS:33645669920

SN - 0932-8092

VL - 17

SP - 83

EP - 93

JO - Machine Vision and Applications

JF - Machine Vision and Applications

IS - 2

ER -