Title :
Video based online behavior detection using probabilistic multi stream fusion
Author :
D. Arsic;W. Bjorn;B. Schuller;G. Rigoll
Author_Institution :
Inst. for Human-Machine-Commun., Technische Univ. Munchen, Germany
fDate :
6/27/1905 12:00:00 AM
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 robustly 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.
Keywords :
"Streaming media","Cameras","Monitoring","Robustness","Microphone arrays","Pattern recognition","Bayesian methods","Video surveillance","Accidents","Costs"
Conference_Titel :
Image Processing, 2005. ICIP 2005. IEEE International Conference on
Print_ISBN :
0-7803-9134-9
DOI :
10.1109/ICIP.2005.1530128