Abstract
With increasing complexity of systems under surveillance, demand grows for automated video-based surveillance systems which are able to support end users in making sense of situational context from the amount of available data and incoming data streams. Traditionally, those systems have been developed based on techniques derived from the fields of image processing and pattern recognition. This paper presents MOSAIC (Multi-Modal Situation Assessment and Analytics Platform), a system which aims at exploiting multi-modal data analysis comprising advanced tools for video analytics, text mining, social network analysis, and decision support in order to provide from a richer context an understanding of behaviour of the system under surveillance and to support police personnel in decision making processes.
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Adderley, R., Badii, A., Evangelio, R.H., Raffaelli, M., Seidler, P., Tiemann, M. (2014). MOSAIC: A Multi-modal Surveillance System to Enhance Situation Awareness and Decision Making. In: Stephanidis, C. (eds) HCI International 2014 - Posters’ Extended Abstracts. HCI 2014. Communications in Computer and Information Science, vol 434. Springer, Cham. https://doi.org/10.1007/978-3-319-07857-1_25
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DOI: https://doi.org/10.1007/978-3-319-07857-1_25
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07856-4
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