Automatic weapon detection using hand poses

F. J. Maigler; J. D. Muñoz; J. Ruiz-Santaquiteria; O. Deniz; G. Bueno; N. Vallez

doi:10.1117/12.3026718

3 October 2024 Automatic weapon detection using hand poses

F. J. Maigler, J. D. Muñoz, J. Ruiz-Santaquiteria, O. Deniz, G. Bueno, N. Vallez

Author Affiliations +

Proceedings Volume 13138, Applications of Machine Learning 2024; 131380V (2024) https://doi.org/10.1117/12.3026718
Event: Optical Engineering + Applications, 2024, San Diego, California, United States

Abstract

Ensuring public safety is a critical concern in our modern society, and as technology advances, so do the methods for enhancing security. While some people develop sophisticated security systems, others seek ways to bypass them. This dynamic necessitates the continuous development of innovative technologies for detecting concealed weapons. In this paper, we compare state-of-the-art methods for automatic weapon detection using computer vision techniques, specifically focusing on hand pose classification. We propose a novel approach that combines hand pose analysis to enhance the accuracy and reliability of weapon detection through camera systems.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

F. J. Maigler, J. D. Muñoz, J. Ruiz-Santaquiteria, O. Deniz, G. Bueno, and N. Vallez "Automatic weapon detection using hand poses", Proc. SPIE 13138, Applications of Machine Learning 2024, 131380V (3 October 2024); https://doi.org/10.1117/12.3026718

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