Machine Learning of motion patterns in the penal system
Violence in prison is no exception: suicides, for example, can be prepared and carried out in unobserved moments. Suicides in prisons often cause collateral damage beyond the tragedy of the event, ranging from increased media coverage to irritation among employees and inmates.
The project will provide important insights for the digitization of the prison regime system and offers the chance to develop highly innovative solutions from Austria for prisons worldwide.
The goals of this project are:
- The definition of behavioral patterns and scenarios in prisons to be detected by a 3D sensor
- Using 3D image analysis to register behavioral patterns of people in real-time to identify critical movement patterns
- Analyzing possibilities for the support of security personnel in prisons by detecting motion patterns
- Development of a prototype
T. Heitzinger and M. Kampel “IPT: A Dataset for Identity Preserved Tracking in Closed Domains”, in Proceedings of the 25th International Conference on Pattern Recognition (ICPR), Milan, Italy, January 2021
C. Pramerdorfer, M. Kampel, R. Kreissl “Behavior Detection as a Privacy-Enhancing Security Technology in Prison Cells”, Proc. 9th International Conference on Imaging for Crime Detection and Prevention (ICDP), London, UK, December 2019
C. Pramerdorfer, M. Kampel, M. Van Loock “Multi-View Classification and 3D Bounding Box Regression Networks“, 24th International Conference on Pattern Recognition (ICPR), pp. 734-739, Beijing, China, August 2018
Das Projekt wird innerhalb des Sicherheitsforschungs-Förderprogramm KIRAS durch das Bundesministeriums für Verkehr, Innovation und Technologie (BMVIT) gefördert.