An increase in visual surveillance systems together with an increased inquiry for security and efficiency leads to the need of efficient systems which are able to process and interpret video data automatically. Based on developments in the area of machine vision, pattern recognition and visual sensors this project deals with the development of a system for automatic event recognition in videostreams, under special consideration of social and cultural aspects. By integrating social-scientific aspects from the beginning a close collaboration with the technical content is granted.
The goal of the project is the development of a system for automated event recognition or so called “abnormal behaviour” detection within security-critical infrastructure. Recognition of certain activities in a scene occurs through the analysis of the acquired image sequences. The planned system concentrates on object tracking with several cameras followed by an event detection, as well as optimised data compression with efficient archiving. Existing methods are adapted and enhanced. The methods investigated are evaluated under realworld conditions, therefore the consumers define certain scenarios in order to install a prototype system: an operational real time processing prototype at the facilities of the end users (Erste Bank sOM Objektmangement) will be implemented. tripleB ID will be implemented on off the shelf IP cameras and computing hardware which will ensure that the technologies and algorithm can be adopted more easily later on. The project will be a key enabler for all end-users to utilize their surveillance technology far beyond the existing possibilities of data storage and/or monitoring by human operator.
This project will be performed in cooperation with:
- CogVis Software und Consulting Gmbh
- Institut f. höhere Studien, IHS
- sOM Objektmanagement GmbH (sOM)
- BMI, Bundeskriminalamt – Abteilung Kriminalprävention und Opferschutz
Zambanini S., Blauensteiner P., Kampel M., “Automated Multi-Camera Surveillance for the Prevention and Investigation of Bank Robberies in Austria: A Case Study” 3rd International Conference on Imaging for Crime Detection and Prevention (ICDP’09), P31, London, Great Britain, December 2009.
Zweng A. “Detecting Unexpected Behavior in Image Sequences” accepted at 34th Workshop of the Austrian Association of Pattern Recognition (OAGM/AAPR10), Zwettl, Austria, May 2010.
Musik C., Vogtenhuber S., Blauensteiner P., Kampel M. “Automated detection of security critical scenarios in bank foyers by image analysis: A review.” accepted at ‘A Global Surveillance Society?‘ Conference, London, Great Britain, April 2010.
Blauensteiner P., Kampel M., Musik, C., Vogtenhuber S. “A Socio-Technical Approach for Event Detection in Security Critical Infrastructure”,Intl. Workshop on Socially Intelligent Surveillance and Monitoring (SISM 2010) in conjunction with IEEE Intl. Conference on Computer Vision and Pattern Recognition (CVPR 2010), San Francisco, CA, USA, Junde 2010., San Francisco, CA, USA, June 2010.