Video analytics is a widely popular tech that automatically analyzes content captured by video cameras. Intelligent algorithms process video data in real-time to generate information on what transpiring in a series of images. Video analytics for security is immensely used to detect and gain insights into the motion of objects, people, and vehicles in CCTV footage.
Actually, video analytics surveillance systems provide a more practical and effective way to review and observe security footage. Content captured by multiple cameras over several days can be automatically sorted by matters of interested, supporting security personnel in identifying and effectively responding to suspicious activities in real-time and during investigations.
When talking about video analytics, there are two main types of systems you need to know about i.e.. traditional video analytics and AI-based video analytics. Basic systems use rule-based algorithms to analyze video content. However, traditional video analytics systems can’t retain information or learn from previously recorded incidents.
AI-based video analytics, on the other hand, also use a rule-based process to gain image insights. But their algorithms use AI and ML tools to help them learn from wider data. In short, deep learning in video analytics enables systems to learn patterns from historical events to improve detection accuracy.
That brings us to the common types of video analytics. One notable type you should be aware of is automatic license plate recognition (ALPR). These cameras use a special type of video analytics called Optical Character Recognition (OCR) to read license plate information on passing vehicles.
This tech can be used in supporting parking management and vehicular access control operations, not forgetting the observation of access roads and parking areas to highlight the presence of suspicious vehicles.
Video analytics algorithms can also be used for crowd detection. These algorithms are programed to identify humans and measure the density of crowds in a camera’s field of view. Crowd detection analytics is used to bolster safety at live events, alerting teams to potential bottlenecks and disturbances that might call for further attention, as well as to track occupancy levels and spot unusual activity.
As we conclude, real-time video analytics offers numerous significant benefits to businesses across most major sectors, allowing professionals to gain actionable insights into important security, infrastructural and organizational processes. Thanks to video analytics, teams can improve security responses, gain insights into business operations and support human workers in performing tasks safely.