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2024 | OriginalPaper | Buchkapitel

Weapon Detection Using PTZ Cameras

verfasst von : Juan Daniel Muñoz, Jesus Ruiz-Santaquiteria, Oscar Deniz, Gloria Bueno

Erschienen in: Robotics, Computer Vision and Intelligent Systems

Verlag: Springer Nature Switzerland

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Abstract

Massive shooting in public places are a stigma in some countries. Computer vision techniques are being actively researched in the last few years to process video from surveillance cameras and immediately detect the presence of an armed individual. The research, however, has focused on images taken from cameras that are (as is the typical case) far from the entrance where the individual first appears. However, most modern video surveillance cameras have some pan-tilt-zoom (PTZ) capabilities, fully controllable by the operator or some control software. In this paper, we make the first (as far as the authors know) exploration on the use of PTZ cameras in this particular problem. Our results unequivocally reveal the transformative impact of integrating PTZ functionality, particularly zoom and tracking capabilities, on the overall performance of these weapon detection models. Experiments were carefully executed in controlled environments, including laboratory and classroom settings, allowing for a comprehensive evaluation. In these settings, the utility of PTZ in improving detection outcomes became evident, especially when confronted with challenging conditions such as dim lighting or multiple individuals in the scene. This research underscores the immense potential of modern PTZ cameras for automatic firearm detection. This advancement holds the promise of augmenting public safety and security.

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Metadaten
Titel
Weapon Detection Using PTZ Cameras
verfasst von
Juan Daniel Muñoz
Jesus Ruiz-Santaquiteria
Oscar Deniz
Gloria Bueno
Copyright-Jahr
2024
DOI
https://doi.org/10.1007/978-3-031-59057-3_7

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