Video Analytics in CCTV Cameras Overview

The term video analytics in CCTV Cameras may seem familiar if you’re into surveillance systems or technology in general. Due to its wide range of applications, the market for this is exhibiting signs of rising expansion. But what precisely are video analytics and why is this technology so much sought after? Find out for yourself by reading on.

What Is the Purpose of Video Analytics in the CCTV Cameras?

For security purposes, video analytics is a system that uses a particular algorithm to process a digital video stream. For example, it is a security technology that uses video analysis to fulfill particular activities. It’s like having an additional pair of eyes to capture key occurrences that you may otherwise miss with standard monitoring, which is why this technology is so valuable. Fixed algorithm analytics, artificial intelligence, learning algorithms, and facial recognition systems are the most frequent forms of video analytics.

Systems for the Recognition of Facial Expressions

It is possible that you are already familiar with face recognition, one of the video analytics. Rather than entering a pin or fingerprint to unlock their iPhone, users may opt to utilize facial recognition instead. Every individual has a distinct face signature, much like fingerprints. Even if you seem like someone else, no two faces are exactly the same. Face recognition uses mathematical measures of a person’s facial trait to identify them.

By comparing the faces collected in CCTV footage to a specified database of registered persons and their images, face recognition in CCTV works as expected. CCTV video analysis is beneficial in a variety of ways. The owner of the business, for example, can receive an alert anytime a shoplifter enters their premises to avoid theft if the store owner has registered the shoplifter in their database.

Fixed-Algorithm Analytical Methods

Due to their shared purpose, fixed algorithms and learning algorithms might be mistaken for one another. We may detect suspicious behavior in CCTV footage using any of these video analytics in CCTV Cameras, but how they do so differ. Fixed algorithm analytics use a set of algorithms to recognize a particular type of behavior. To put it another way, there is an algorithm for every possible behavior. As the name suggests, each of these algorithms has a set goal in mind.

There are several fixed methods for detecting certain behaviors, however, the following are some of the most frequent ones:

• A movement that appears to cross an imaginary line, which can be a sign of incursion
• Counting people
• Detecting the movement’s direction (useful for identifying cars driving on the wrong side of the road)
• We can monitor certain locations for the presence of idle things (we can use it to identify people loitering around a business or suspicious luggage abandoned in an airport)

Algorithms for Machine Learning With The Video Analytics In CCTV Cameras

Learning algorithms for artificial intelligence (AI) are a type of video analysis that relies on experience to work. They arrive with no pre-installed algorithms; instead, they’re empty slots.  We’ve already discussed object recognition as an example of this. In object recognition, the machine is continually exposed to diverse items in order to learn how to identify and recognize objects. When it comes to spotting possible threats like weapons or tracing the path of an object, object recognition comes in handy.

Using artificial intelligence to learn about what is usual in certain locations and at specific times can also assist to improve security. An airport installed a camera to monitor the loading of baggage onto a carousel. It was only feasible because the system learned what is normal and what isn’t via experience.

FAQ (Frequently Asked Questions)