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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Acknowledgements
This work is part of project DISARM, Grant PDC2021-121197, funded by MCIN/AEI/ 10.13039/501100011033 and “European Union NextGenerationEU/PRTR”. The work has been partially funded by the following projects: SBPLY/21/180501/000025 by the Autonomous Government of Castilla-La Mancha and the European Regional Development Fund (ERDF), and dAIEdge Grant n. 101120726 by the European Commission. Author J. Ruiz-Santaquiteria was supported by Postgraduate Grant from the Spanish Ministry of Science, Innovation, and Universities (grant number PRE2018-083772).
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Muñoz, J.D., Ruiz-Santaquiteria, J., Deniz, O., Bueno, G. (2024). Weapon Detection Using PTZ Cameras. In: Filipe, J., Röning, J. (eds) Robotics, Computer Vision and Intelligent Systems. ROBOVIS 2024. Communications in Computer and Information Science, vol 2077. Springer, Cham. https://doi.org/10.1007/978-3-031-59057-3_7
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