DocumentCode :
3619840
Title :
Video Based Online Behavior Detection Using Probabilistic Multi Stream Fusion
Author :
D. Arsic;F. Wallhoff;B. Schuller;G. Rigoll
Author_Institution :
Institute for Human-Machine-Communication, Faculty of Electrical Enfineering, Technische Universitä
fYear :
2005
fDate :
6/27/1905 12:00:00 AM
Firstpage :
1354
Lastpage :
1357
Abstract :
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 sub-tasks 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
Keywords :
"Streaming media","Cameras","Face detection","Monitoring","Robustness","Microphone arrays","Infrared detectors","Pattern recognition","Bayesian methods","Video surveillance"
Publisher :
ieee
Conference_Titel :
Multimedia and Expo, 2005. ICME 2005. IEEE International Conference on
Print_ISBN :
0-7803-9331-7
Type :
conf
DOI :
10.1109/ICME.2005.1521681
Filename :
1521681
Link To Document :
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