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1.	Brax, Christoffer, et al. (author) Finding behavioural anomalies in public areas using video surveillance data 2008 In: Proceedings of the 11th International Conference on Information Fusion. - : IEEE. - 9783000248832 - 9783800730926 ; , s. 1655-1662 Conference paper (peer-reviewed)abstract 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.

Brax, Christoffer, et al. (author)
Finding behavioural anomalies in public areas using video surveillance data
2008
In: Proceedings of the 11th International Conference on Information Fusion. - : IEEE. - 9783000248832 - 9783800730926 ; , s. 1655-1662
Conference paper (peer-reviewed)abstract
- 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.

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