A hierarchical approach for visual suspicious behavior detection in aircrafts

Authors:
D. Arsic;B. Hörnler;B. Schuller;G. Rigoll
Affiliations:
Institute for Human Machine Communication, Technische Universität München, Germany;Institute for Human Machine Communication, Technische Universität München, Germany;Institute for Human Machine Communication, Technische Universität München, Germany;Institute for Human Machine Communication, Technische Universität München, Germany
Venue:
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
Year:
2009

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Abstract

Recently great interest has been shown in the visual surveillance of public transportation systems. The challenge is the automated analysis of passenger's behaviors with a set of visual low-level features, which can be extracted robustly. On a set of global motion features computed in different parts of the image, here the complete image, the face and skin color regions, a classification with Support Vector Machines is performed. Test-runs on a database of aggressive, cheerful, intoxicated, nervous, neutral and tired behavior.