TY - GEN
T1 - Suspicious behavior detection in public transport by fusion of low-level video descriptors
AU - Arsić, Dejan
AU - Schuller, Björn
AU - Rigoll, Gerhard
PY - 2007
Y1 - 2007
N2 - 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 in an airplane situation show promising results.
AB - 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 in an airplane situation show promising results.
KW - Behavior detection
KW - Feature fusion
KW - Low level features
KW - Video surveillance
UR - http://www.scopus.com/inward/record.url?scp=46449102692&partnerID=8YFLogxK
U2 - 10.1109/icme.2007.4285076
DO - 10.1109/icme.2007.4285076
M3 - Conference contribution
AN - SCOPUS:46449102692
SN - 1424410177
SN - 9781424410170
T3 - Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007
SP - 2018
EP - 2021
BT - Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007
PB - IEEE Computer Society
T2 - IEEE International Conference onMultimedia and Expo, ICME 2007
Y2 - 2 July 2007 through 5 July 2007
ER -