Title :
A bio-inspired knowledge representation method for anomaly detection in cognitive Video Surveillance systems
Author :
Chiappino, Simone ; Morerio, Pietro ; Marcenaro, Lucio ; Regazzoni, C.S.
Author_Institution :
DITEN, Univ. of Genoa, Genoa, Italy
Abstract :
Human behaviour analysis has important applications in the field of anomaly management, such as Intelligent Video Surveillance (IVS). As the number of individuals in a scene increases, however, new macroscopic complex behaviours emerge from the underlying interaction network among multiple agents. This phenomenon has lately been investigated by modelling such interaction through Social Forces.
Keywords :
knowledge representation; multi-agent systems; video surveillance; IVS; anomaly detection; anomaly management; bio-inspired knowledge representation method; cognitive video surveillance systems; human behaviour analysis; intelligent video surveillance; macroscopic complex behaviours; multiple agents; social forces; Biological system modeling; Mathematical model; Probabilistic logic; Training; Vectors; Video surveillance; Anomalous interactions; Bio-inspired learning; Cognitive systems; Crowd monitoring;
Conference_Titel :
Information Fusion (FUSION), 2013 16th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-605-86311-1-3
