Abstract
| Original language | English |
|---|---|
| Title of host publication | Proceedings International Joint Conference on Neural Networks (IJCNN), 6-11 July, 2014, Beijing, China |
| Place of Publication | Piscataway |
| Publisher | Institute of Electrical and Electronics Engineers |
| Pages | 3966-3973 |
| ISBN (Print) | 978-1-4799-1484-5 |
| DOIs | |
| Publication status | Published - 2014 |
| Event | 2014 International Joint Conference on Neural Networks (IJCNN 2014), July 6-11, 2014, Beijing, China - Beijing International Convention Center, Beijing, China Duration: 6 Jul 2014 → 11 Jul 2014 http://www.ieee-wcci2014.org |
Conference
| Conference | 2014 International Joint Conference on Neural Networks (IJCNN 2014), July 6-11, 2014, Beijing, China |
|---|---|
| Abbreviated title | IJCNN 2014 |
| Country | China |
| City | Beijing |
| Period | 6/07/14 → 11/07/14 |
| Other | International Joint Conference on Neural Networks |
| Internet address |
Fingerprint
Cite this
}
Bio-inspired probabilistic model for crowd emotion detection. / Baig, M.W.; Barakova, E.I.; Marcenaro, L.; Regazzoni, C.S.; Rauterberg, G.W.M.
Proceedings International Joint Conference on Neural Networks (IJCNN), 6-11 July, 2014, Beijing, China. Piscataway : Institute of Electrical and Electronics Engineers, 2014. p. 3966-3973.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
TY - GEN
T1 - Bio-inspired probabilistic model for crowd emotion detection
AU - Baig, M.W.
AU - Barakova, E.I.
AU - Marcenaro, L.
AU - Regazzoni, C.S.
AU - Rauterberg, G.W.M.
PY - 2014
Y1 - 2014
N2 - Detection of emotions of a crowd is a new research area, which has never, to our knowledge, been accounted for research in previous literature. A bio-inspired model for representation of emotional patterns in crowds has been demonstrated. Emotions have been defined as evolving patterns as part of a dynamic pattern of events. This model has been developed to detect emotions of a crowd based on the knowledge from a learned context, psychology and experience of people in crowd management. The emotions of multiple people making a crowd in any surveillance environment are estimated by sensors signals such as a camera and are being tracked and their behavior is modeled using bio-inspired dynamic model. The behavior changes correspond to changes in emotions. The proposed algorithm involves the probabilistic signal processing modelling techniques for analysis of different types of behavior, interaction detection and estimation of emotions. The emotions are recognized by the expectation of temporal occurrences of causal events modeled by Gaussian mixture model. The model has been evaluated using the simulated behavioral model of a crowd.
AB - Detection of emotions of a crowd is a new research area, which has never, to our knowledge, been accounted for research in previous literature. A bio-inspired model for representation of emotional patterns in crowds has been demonstrated. Emotions have been defined as evolving patterns as part of a dynamic pattern of events. This model has been developed to detect emotions of a crowd based on the knowledge from a learned context, psychology and experience of people in crowd management. The emotions of multiple people making a crowd in any surveillance environment are estimated by sensors signals such as a camera and are being tracked and their behavior is modeled using bio-inspired dynamic model. The behavior changes correspond to changes in emotions. The proposed algorithm involves the probabilistic signal processing modelling techniques for analysis of different types of behavior, interaction detection and estimation of emotions. The emotions are recognized by the expectation of temporal occurrences of causal events modeled by Gaussian mixture model. The model has been evaluated using the simulated behavioral model of a crowd.
U2 - 10.1109/IJCNN.2014.6889964
DO - 10.1109/IJCNN.2014.6889964
M3 - Conference contribution
SN - 978-1-4799-1484-5
SP - 3966
EP - 3973
BT - Proceedings International Joint Conference on Neural Networks (IJCNN), 6-11 July, 2014, Beijing, China
PB - Institute of Electrical and Electronics Engineers
CY - Piscataway
ER -