Detecting abandoned objects using interacting multiple models

Stefan Becker; David Münch; Hilke Kieritz; Wolfgang Hübner; Michael Arens

doi:10.1117/12.2195224

21 October 2015 Detecting abandoned objects using interacting multiple models

Stefan Becker, David Münch, Hilke Kieritz, Wolfgang Hübner, Michael Arens

Proceedings Volume 9652, Optics and Photonics for Counterterrorism, Crime Fighting, and Defence XI; and Optical Materials and Biomaterials in Security and Defence Systems Technology XII; 96520G (2015) https://doi.org/10.1117/12.2195224
Event: SPIE Security + Defence, 2015, Toulouse, France

Abstract

In recent years, the wide use of video surveillance systems has caused an enormous increase in the amount of data that has to be stored, monitored, and processed. As a consequence, it is crucial to support human operators with automated surveillance applications. Towards this end an intelligent video analysis module for real-time alerting in case of abandoned objects in public spaces is proposed. The overall processing pipeline consists of two major parts. First, person motion is modeled using an Interacting Multiple Model (IMM) filter. The IMM filter estimates the state of a person according to a finite-state, discrete-time Markov chain. Second, the location of persons that stay at a fixed position defines a region of interest, in which a nonparametric background model with dynamic per-pixel state variables identifies abandoned objects. In case of a detected abandoned object, an alarm event is triggered. The effectiveness of the proposed system is evaluated on the PETS 2006 dataset and the i-Lids dataset, both reflecting prototypical surveillance scenarios.

Citation Download Citation

Stefan Becker, David Münch, Hilke Kieritz, Wolfgang Hübner, and Michael Arens "Detecting abandoned objects using interacting multiple models", Proc. SPIE 9652, Optics and Photonics for Counterterrorism, Crime Fighting, and Defence XI; and Optical Materials and Biomaterials in Security and Defence Systems Technology XII, 96520G (21 October 2015); https://doi.org/10.1117/12.2195224

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