Video analytics is a tech that observes and analyzes recorded content to change real-time information into intelligent and actionable insights. Smart video analytics for security systems leverage specialized AI and machine learning technologies to continuously observe video footage, with programs that are configured to automatically detect malicious and anomalous events.
This ensures video security systems identify and observer different objects and stimuli associated with security without help from human operators. For instance, video analytics systems can autonomously detect and observe cars, persons of interest, contraband items and unusual objects, issuing warning to staff of events that call for attention.
Video content analytics systems work by counting on rule-based algorithms to discern whether stimuli in live surveillance footage pose any risks or threats. Software tools will pose and answer a couple of questions in an ‘if/then’ decision tree.
CCTV analytics systems keep a close eye on live footage by isolating individual frames and inspecting the images in sequence. Rule-based algorithms continuously analyze the footage pertaining to the afore-mentioned tree, recording all changes in the form of intelligent metadata.
Well, this allows for deep learning in video content analytics with the process helping to bolster threat detection capabilities. Eventually, AI tools learn patterns in data that then inform the operation of surveillance systems.
It is worth mentioning that there are different types of video analytics in CCTV worth keeping a close eye on. Among the most notable ones include License Plate Recognition (LPR), Facial Recognition (FR), occupancy counting, and object detection.
License Plater Recognition uses a combination of Optical Character Recognition (OCR) software and video analytics technologies to detect and analyze license plate data from passing vehicles. Video analytics algorithms assess the shape, size, and movement traits of any object that passes past the camera. The essence of doing this is to determine if the target is likely to be a car or not.
With facial recognition scans, they can be used for a host of purposes. For instance, they can be used as access credentials to control entry to high-security locations, or even observe buildings in search of known offenders.
All in all, video surveillance analytics have immensely transformed how modern businesses approach commercial security and building management. From enhanced threat detection and incident response capabilities to the generation of high-quality data insights, video content analytics helps support teams across most major industries.
