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Finding behavioural anomalies in public areas using video surveillance data
Högskolan i Skövde, Institutionen för kommunikation och information. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
Högskolan i Skövde, Institutionen för kommunikation och information. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
Saab Microwave Systems, Saab AB, Gothenburg, Sweden.
2008 (engelsk)Inngår i: Proceedings of the 11th International Conference on Information Fusion, IEEE conference proceedings, 2008, s. 1655-1662Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

 In this paper we propose an approach forvdetecting anomalies in data from visual surveillancevsensors. The approach includes creating a structure for representing data, building “normal models” by filling the structure with data for the situation at hand, and finally detecting deviations in the data. The approach allows detections based on the incorporation of a priori knowledge about the situation and on data-driven analysis. The main advantages with the approach compared to earlier work is the low computational requirements, iterative update of normal models and a high explainability of found anomalies. The proposed approach is evaluated off-line using real-world data and the results support that the approach could be used to detect anomalies in real-time applications.

 

sted, utgiver, år, opplag, sider
IEEE conference proceedings, 2008. s. 1655-1662
Emneord [en]
Anomaly detection, visual surveillance, behaviour modelling
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URN: urn:nbn:se:his:diva-3607DOI: 10.1109/ICIF.2008.4632410Scopus ID: 2-s2.0-56749117785ISBN: 978-3-00-024883-2 OAI: oai:DiVA.org:his-3607DiVA, id: diva2:291095
Tilgjengelig fra: 2010-01-29 Laget: 2010-01-29 Sist oppdatert: 2017-11-27

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