Detection of infrastructure manipulation with knowledge-based video surveillance

David Muench; Barbara Hilsenbeck; Hilke Kieritz; Stefan Becker; Ann-Kristin Grosselfinger; Wolfgang Huebner; Michael Arens

doi:10.1117/12.2240304

24 October 2016 Detection of infrastructure manipulation with knowledge-based video surveillance

David Muench, Barbara Hilsenbeck, Hilke Kieritz, Stefan Becker, Ann-Kristin Grosselfinger, Wolfgang Huebner, Michael Arens

Author Affiliations +

Proceedings Volume 9995, Optics and Photonics for Counterterrorism, Crime Fighting, and Defence XII; 99950P (2016) https://doi.org/10.1117/12.2240304
Event: SPIE Security + Defence, 2016, Edinburgh, United Kingdom

Abstract

We are living in a world dependent on sophisticated technical infrastructure. Malicious manipulation of such critical infrastructure poses an enormous threat for all its users. Thus, running a critical infrastructure needs special attention to log the planned maintenance or to detect suspicious events. Towards this end, we present a knowledge-based surveillance approach capable of logging visual observable events in such an environment. The video surveillance modules are based on appearance-based person detection, which further is used to modulate the outcome of generic processing steps such as change detection or skin detection. A relation between the expected scene behavior and the underlying basic video surveillance modules is established. It will be shown that the combination already provides sufficient expressiveness to describe various everyday situations in indoor video surveillance. The whole approach is qualitatively and quantitatively evaluated on a prototypical scenario in a server room.

Citation Download Citation

David Muench, Barbara Hilsenbeck, Hilke Kieritz, Stefan Becker, Ann-Kristin Grosselfinger, Wolfgang Huebner, and Michael Arens "Detection of infrastructure manipulation with knowledge-based video surveillance", Proc. SPIE 9995, Optics and Photonics for Counterterrorism, Crime Fighting, and Defence XII, 99950P (24 October 2016); https://doi.org/10.1117/12.2240304

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