Paper
19 May 2011 An implicit shape model based approach to identify armed persons
Stefan Becker, Kai Jüngling
Author Affiliations +
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.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Stefan Becker and Kai Jüngling "An implicit shape model based approach to identify armed persons", Proc. SPIE 8049, Automatic Target Recognition XXI, 80490O (19 May 2011); https://doi.org/10.1117/12.883658
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KEYWORDS
Weapons

Prototyping

Sensors

Feature extraction

Thermal modeling

Data modeling

Image classification

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