Introduction
Many regions have a high rate of crime caused by weapons, especially in areas where they are permitted. As a result when crimes are committed, elements involved become evidence which needs to be gathered. Often this evidence is digital, which includes elements such as CCTV recordings. With ever increasing crime rates, organizations feel the need to automatically detect the presence of dangerous weapons such as pistols, rifles, shotguns, etc. in surveillance videos to increase the searchability of weapons within a video, which appears at different time stamps. With better detection capabilities, criminal activity can be stopped in its tracks before much harm is done.
While the world still believes human monitoring and intervention are still required by current surveillance and control systems to identify weapons in videos. VIDIZMO offers the capability to automatically detect firearms in video, which can be used for monitoring and control.
VIDIZMO, in combination with its all-encompassing, robust video content management capabilities, has built AI Indexer to provide enterprises with the power to detect weapons automatically within the videos.
Concept
Automatic weapon detection employs machine learning algorithms to detect weapons across a single class i.e., "gun" in videos that frequently include cross crime scenes from CCTV footages mainly. This automatic Weapon Detection technique enables VIDIZMO indexer to read weapons quickly and automatically, without the need for human intervention.
VIDIZMO takes videos captured that may contain weapons or CCTV video recordings containing weapons as input. The indexer takes the video and detects weapons that appear within the video at different timestamps with different angle views and classifies them as "gun".
VIDIZMO indexer takes video as input. Indexer starts a workflow activity that takes some time to detect weapons in video. Video processing time may vary as it depends on factors such as video quality, duration, and resolution. Once the detection is complete, the user can see the detected weapons by navigating to Studio Space and redact all the detected weapons.
To understand redaction in detail, please refer to this article: Understanding Redaction using Studio Space. In order to redact the automatically detected license plates, please refer to this article: How to Redact PII from Digital Evidences.
Moreover, VIDIZMO Indexer also gives the flexibility to choose from three different models, which are "Small", "Medium", and "Large". It also allows the user to set confidence threshold, tracking frame based on which the indexer will detect license plates so that the user is able to get most out of the VIDIZMO Indexer capability according to the use case.
Please refer to the following article to understand what model size, confidence threshold, and tracking frames are: How to configure VIDIZMO Indexer for object detection
Detection
VIDIZMO Indexer's Automatic Weapon Detection capability offers numerous advantages that are the basis for real-world scenarios. The majority of its advantages are related to automating manual jobs and governance. Some of the advantages, VIDIZMO indexer offers for Automatic Weapon Detection are listed below:
Performance
Human input is not required for precise and fast weapon detection. As a result, it promotes cost-effective governance and shortens wait times. VIDIZMO Indexer detects all the weapons with maximum accuracy in short span of time.
Night and Daytime lightning conditions
Weapons, specifically guns, in daytime and night are efficiently detected. As a result, it promotes higher detection accuracy and less manual work.
Contributions were made by Nabeel Ali & Mir Wahaj.
Read Next:
Understanding Redaction Using Studio Space
How to Redact PII From Digital Evidences
Understanding Automatic License Plate Recognition (ALPR)
How to configure VIDIZMO Indexer for object detection
Understanding Automatic Vehicle Detection