Bio-inspired probabilistic model for crowd emotion detection

M.W. Baig, E.I. Barakova, L. Marcenaro, C.S. Regazzoni, G.W.M. Rauterberg

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

7 Citations (Scopus)


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.
Original languageEnglish
Title of host publicationProceedings International Joint Conference on Neural Networks (IJCNN), 6-11 July, 2014, Beijing, China
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
ISBN (Print)978-1-4799-1484-5
Publication statusPublished - 2014
Event2014 International Joint Conference on Neural Networks (IJCNN 2014), July 6-11, 2014, Beijing, China - Beijing International Convention Center, Beijing, China
Duration: 6 Jul 201411 Jul 2014


Conference2014 International Joint Conference on Neural Networks (IJCNN 2014), July 6-11, 2014, Beijing, China
Abbreviated titleIJCNN 2014
OtherInternational Joint Conference on Neural Networks
Internet address

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