What is Weapon Detection?
Weapon detection with AI and deep learning technologies is used for security applications. Such vision-based systems can recognize and interpret scenes using the footage of video surveillance systems. AI vision methods are used to recognize knives and guns with the goal to reduce crimes and increase safety and security.
In traditional video surveillance, security agents have to visually detect the presence of weapons in monitored scenes by watching security footage and quickly make decisions based on it. One of the most effective solutions to overcome the shortcomings of manual analysis is to process the real-time video stream of surveillance cameras with deep learning algorithms to automate weapon detection at higher accuracy.
The Key Features
Weapon detection systems use high-performance object detection algorithms using deep neural networks:
- Automatically detect automatic guns and firearms using deep learning models.
- Detection of knives and sharp cold steel weapons in video surveillance footage.
- Real-world use in highly populated and complex scenes.
- Activation of an alarm in real-time with information about the weapon’s location.
- Weapon identification and classification to aid further investigation by security personnel.
Value of Automated Weapon Detection
Machine learning based weapon detection is comparably robust and allows higher safety and security in public places.
- The automation of weapon detection is more consistent and faster than manual review.
- Increased safety and anomaly event monitoring in crowded events or public places.
- In mission-critical situations, such systems flag critical situations for immediate human review.
- Computer vision based weapon detection is highly scalable and can operate with a high number of cameras and in complex and crowded scenes.
