MARIE: One-Stage Object Detection Mechanism for Real-Time Identifying of Firearms

Diana Abi-Nader¹, Hassan Harb², Ali Jaber¹, Ali Mansour³, Christophe Osswald³, Nour Mostafa^2,*, Chamseddine Zaki²
1 Computer Science Department, Faculty of Sciences, Lebanese University, Beirut, 146404, Lebanon
2 College of Engineering and Technology, American University of the Middle East, Egaila, 54200, Kuwait
3 Lab-STICC, CNRS UMR 6285, ENSTA-Bretagne, Brest, 29200, France
* Corresponding Author: Nour Mostafa. Email: email

Computer Modeling in Engineering & Sciences https://doi.org/10.32604/cmes.2024.056816

Received 31 July 2024; Accepted 24 October 2024; Published online 19 November 2024

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Abstract

Security and safety remain paramount concerns for both governments and individuals worldwide. In today’s context, the frequency of crimes and terrorist attacks is alarmingly increasing, becoming increasingly intolerable to society. Consequently, there is a pressing need for swift identification of potential threats to preemptively alert law enforcement and security forces, thereby preventing potential attacks or violent incidents. Recent advancements in big data analytics and deep learning have significantly enhanced the capabilities of computer vision in object detection, particularly in identifying firearms. This paper introduces a novel automatic firearm detection surveillance system, utilizing a one-stage detection approach named MARIE (Mechanism for Real-time Identification of Firearms). MARIE incorporates the Single Shot Multibox Detector (SSD) model, which has been specifically optimized to balance the speed-accuracy trade-off critical in firearm detection applications. The SSD model was further refined by integrating MobileNetV2 and InceptionV2 architectures for superior feature extraction capabilities. The experimental results demonstrate that this modified SSD configuration provides highly satisfactory performance, surpassing existing methods trained on the same dataset in terms of the critical speed-accuracy trade-off. Through these innovations, MARIE sets a new standard in surveillance technology, offering a robust solution to enhance public safety effectively.

Keywords

Firearm and gun detection; single shot multi-box detector; deep learning; one-stage detector; MobileNet; inception; convolutional neural network

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MARIE: One-Stage Object Detection Mechanism for Real-Time Identifying of Firearms

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