TY - GEN
T1 - A joint system for person tracking and face detection
AU - Zhang, Zhenqiu
AU - Potamianos, Gerasimos
AU - Senior, Andrew
AU - Chu, Stephen
AU - Huang, Thomas S.
PY - 2005
Y1 - 2005
N2 - Visual detection and tracking of humans in complex scenes is a challenging problem with a wide range of applications, for example surveillance and human-computer interaction. In many such applications, time-synchronous views from multiple calibrated cameras are available, and both frame-view and space-level human location information is desired. In such scenarios, efficiently combining the strengths of face detection and person tracking is a viable approach that can provide both levels of information required and improve robustness. In this paper, we propose a novel vision system that detects and tracks human faces automatically, using input from multiple calibrated cameras. The method uses an Adaboost algorithm variant combined with mean shift tracking applied on single camera views for face detection and tracking, and fuses the results on multiple camera views to check for consistency and obtain the three-dimensional head estimate. We apply the proposed system to a lecture scenario in a smart room, on a corpus collected as part of the CHIL European Union integrated project. We report results on both frame-level face detection and three-dimensional head tracking. For the latter, the proposed algorithm achieves similar results with the IBM "PeopleVision" system.
AB - Visual detection and tracking of humans in complex scenes is a challenging problem with a wide range of applications, for example surveillance and human-computer interaction. In many such applications, time-synchronous views from multiple calibrated cameras are available, and both frame-view and space-level human location information is desired. In such scenarios, efficiently combining the strengths of face detection and person tracking is a viable approach that can provide both levels of information required and improve robustness. In this paper, we propose a novel vision system that detects and tracks human faces automatically, using input from multiple calibrated cameras. The method uses an Adaboost algorithm variant combined with mean shift tracking applied on single camera views for face detection and tracking, and fuses the results on multiple camera views to check for consistency and obtain the three-dimensional head estimate. We apply the proposed system to a lecture scenario in a smart room, on a corpus collected as part of the CHIL European Union integrated project. We report results on both frame-level face detection and three-dimensional head tracking. For the latter, the proposed algorithm achieves similar results with the IBM "PeopleVision" system.
UR - http://www.scopus.com/inward/record.url?scp=33646687263&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33646687263&partnerID=8YFLogxK
U2 - 10.1007/11573425_5
DO - 10.1007/11573425_5
M3 - Conference contribution
AN - SCOPUS:33646687263
SN - 3540296204
SN - 9783540296201
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 47
EP - 59
BT - Computer Vision in Human-Computer Interaction - ICCV 2005 Workshop on HCI, Proceedings
PB - Springer
T2 - ICCV 2005 Workshop on HCI - Computer Vision in Human-Computer Interaction
Y2 - 21 October 2005 through 21 October 2005
ER -