TY - GEN
T1 - Video based online behavior detection using probabilistic multi stream fusion
AU - Arsić, Dejan
AU - Wallhoff, Frank
AU - Schuller, Björn
AU - Rigoll, Gerhard
PY - 2005
Y1 - 2005
N2 - In the present treatise, we propose an approach for a highly configurable image based online person behaviour monitoring system. The particular application scenario is a crew supporting multi-stream on-board threat detection system, which is getting more desirable for the use in public transport. For such frameworks, to work robust in mostly unconstrained environments, many subsystems have to be employed. Although the research field of pattern recognition has brought up reliable approaches for several involved subtasks in the last decade, there often exists a gap between reliability and the needed computational efforts. However in order, to accomplish this highly demanding task, several straight forward technologies, here the output of several so-called weak classifiers using low-level features are fused by a sophisticated Bayesian Network.
AB - In the present treatise, we propose an approach for a highly configurable image based online person behaviour monitoring system. The particular application scenario is a crew supporting multi-stream on-board threat detection system, which is getting more desirable for the use in public transport. For such frameworks, to work robust in mostly unconstrained environments, many subsystems have to be employed. Although the research field of pattern recognition has brought up reliable approaches for several involved subtasks in the last decade, there often exists a gap between reliability and the needed computational efforts. However in order, to accomplish this highly demanding task, several straight forward technologies, here the output of several so-called weak classifiers using low-level features are fused by a sophisticated Bayesian Network.
UR - http://www.scopus.com/inward/record.url?scp=33750570196&partnerID=8YFLogxK
U2 - 10.1109/ICME.2005.1521681
DO - 10.1109/ICME.2005.1521681
M3 - Conference contribution
AN - SCOPUS:33750570196
SN - 0780393325
SN - 9780780393325
T3 - IEEE International Conference on Multimedia and Expo, ICME 2005
SP - 1354
EP - 1357
BT - IEEE International Conference on Multimedia and Expo, ICME 2005
T2 - IEEE International Conference on Multimedia and Expo, ICME 2005
Y2 - 6 July 2005 through 8 July 2005
ER -