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Proceedings Paper

An implicit shape model based approach to identify armed persons
Author(s): Stefan Becker; Kai Jüngling
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Paper Abstract

In addition to detecting and tracking persons via video surveillance in public spaces like airports and train stations, another important aspect of a situation analysis is the appearance of objects in the periphery of a person. Not only from a military perspective, in certain environments, an unidentified armed person can be an indicator for a potential threat. In order to become aware of an unidentified armed person and to initiate counteractive measures, the ability to identify persons carrying weapons is needed. In this paper we present a classification approach, which fits into an Implicit Shape Model (ISM) based person detection and is capable to differentiate between unarmed persons and persons in an aiming body posture. The approach relies on SIFT features and thus is completely independent of sensor-specific features which might only be perceivable in the visible spectrum. For person representation and detection, a generalized appearance codebook is used. Compared to a stand-alone person detection strategy with ISM, an additional training step is introduced that allows interpretation of a person hypothesis delivered by the ISM. During training, the codebook activations and positions of participated features are stored for the desired classes, in this case, persons in an aiming posture and unarmed persons. With the stored information, one is able to calculate weight factors for every feature participating in a person hypothesis in order to derive a specific classification model. The introduced model is validated using an infrared dataset which shows persons in aiming and non-aiming body postures from different angles.

Paper Details

Date Published: 19 May 2011
PDF: 10 pages
Proc. SPIE 8049, Automatic Target Recognition XXI, 80490O (19 May 2011); doi: 10.1117/12.883658
Show Author Affiliations
Stefan Becker, Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (Germany)
Kai Jüngling, Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (Germany)

Published in SPIE Proceedings Vol. 8049:
Automatic Target Recognition XXI
Firooz A. Sadjadi; Abhijit Mahalanobis, Editor(s)

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