Using Computer Vision for Video Surveillance: An All-In-One Handbook

Janmey Solanki

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Summary: From your regular CCTV cameras to automated security drones, video surveillance has come a long way. This blog discusses how computer vision AI revolutionizes video surveillance, making it meticulous and more effective.

With rising security threats, the need for advanced video surveillance has become critical.

Today, surveillance cameras are no longer limited to high-security areas such as nuclear power plants or military installations. They are everywhere – from airports, corporate offices, shopping malls to private buildings.

These numerous cameras collect an incredible amount of random visual data every day. Monitoring, examining, and analyzing such mammoth inputs is humanly impossible.

That’s where computer vision AI enters the picture.

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Computer Vision: The Future of Video Surveillance

Computer Vision AI is a sub-category of artificial intelligence (AI) that enables video surveillance systems to capture, understand, and derive meaningful insights from random digital visual inputs.

It uses AI and deep learning to analyze video footage to identify and notify the unauthorized presence of humans, vehicles, and objects.

Overcoming Human Limitations with Computer Vision

Staring endlessly at camera views of empty corridors, parking lots, or hallways can be exceedingly tedious. Such overwhelming visual monotony makes the human attention span shorter.

The result: increased chances of judgemental errors and inability to recognize a potential risk.

Also, legacy surveillance cameras are reactive. This means you can only react to a situation once the incident has happened. It requires constant human supervision to discern abnormal patterns or anomalous movement before an unfortunate event. For example, law enforcement can gather circumstantial evidence but can’t prevent vandalism.

Integrating computer vision AI enables real-time alerts, notifying the concerned personnel of unauthorized activities, possible intrusion, or other safety breaches- ranging from theft to mass shoot-outs. In this case, the security operatives have enough time to respond and avert any mishaps proactively.

In a way, computer vision technology is like a tap on the shoulder that prompts you to look at something peculiar.

Let’s take a quick look at some of the advantages of computer vision AI in video surveillance:

How Computer Vision Can Help You Achieve Your Video Surveillance Goals: The Benefits

1. Automate Time-Consuming Tasks

Video surveillance generates massive volumes of visual data that requires continuous monitoring by security professionals. This consumes huge amounts of human time and effort.

AI-powered computer vision can automate many tedious and repetitive video analytics tasks. For instance, instead of manually counting people, AI can accurately track foot traffic automatically.

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Computer vision can also autonomously monitor restricted areas 24/7 to detect unauthorized access. It can help with license plate recognition, detecting loitering, or left objects. This automation enables human operators to focus on more critical safety issues rather than watching uneventful footage.

Overall, AI automation enhances productivity, optimizes human resources, and reduces costs for surveillance operations.

2. Recognize Abnormal Behavioural Patterns

Deep learning algorithms classify and observe people, objects, and patterns to create a distinct definition of what is normal. Computer vision AI learns the average behavioral pattern of the objects examined and analyzed.

This makes it possible to recognize any disparity or break in the patterns.

Let’s see an example to get a better perspective. Computer vision AI will alert the operators if it notice an animal or intruder trying to trespass on a protected storage facility at night.

For AI, this is an abnormal pattern, as usually there should be no one at the hour. It may not be possible for humans to continuously supervise a storage area during the night.

Monitoring busy public areas such as airports, shopping malls, and academic campuses to see if someone is carrying a weapon is impractical and ineffective.

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AI-enabled video surveillance cautions security personnel if someone enters carrying a gun or knife, giving them enough time to tackle the situation before it is too late.

3. Actionable Security and Safety Insights

The use of AI cameras goes beyond live footage capture and surveillance. Computer vision technology can examine tons of visual inputs to extract data-driven and actionable insights.

With built-in machine learning, smart motion detection, and object classification, AI camera surveillance can continuously learn and improve. The more data it processes, the more it gets familiar with the “normal behavior and patterns.”

Over time, AI algorithms accumulate insights about regular patterns of activity, making it possible for security teams to make strategic and informed decisions as needed.

4. Prevent Crime and Liability Risks

With continuous real-time monitoring, AI-enabled surveillance systems can help deter criminal activities and legal risks. Criminals are less likely to attempt theft, vandalism or other offenses if they know the area is under active surveillance.

Computer vision analytics like crowd density estimation, object left behind detection can alert operators about suspicious behaviors. This allows preventative action rather than just reactive response.

AI surveillance data provides visual evidence if any incident occurs. This is invaluable for investigating insurance claims or legal disputes. Demonstrable footage confirms alibis and reduces liability risks.

Overall, proactive AI monitoring creates a strong deterrence against crimes, frauds and unethical activities. Smart surveillance safeguards people, assets and brand reputation 24/7 with minimal human intervention needed.

How Computer Vision AI Video Surveillance is Transforming Industries

1. Manufacturing Units and Warehouses

Manufacturing units and warehouses can employ computer vision camera surveillance to prevent intrusion, theft, and unauthorized access. Also, these cameras can help in gathering business intelligence and streamline and automate security operations.

2. Energy Sector

The energy sector can employ AI video surveillance to monitor prohibited and restricted areas like power plants, pipelines, and critical infrastructure to avert trespassing and ensure safety.

3. Supply Chain and Logistics

The supply chain and logistics industry can use embedded vision technology for camera surveillance to deter nefarious acts such as thefts or intrusion. Additionally, this industry can leverage AI-powered cameras to recognize abnormal patterns to prevent any mishap before it can go out of control.

4. Retail Industry

From curbing shoplifting to enhancing customer experience, AI-powered camera surveillance can help the retail industry in several ways.

5. Transport Industry

Computer vision AI uses deep learning algorithms to analyze video footage to monitor critical elements within the field of view and identify any inconsistencies in normal behavior. This helps security operatives take appropriate safety measures.

How AI is Revolutionizing Video Surveillance

There is no denying that the future of video surveillance is AI-enabled. Currently, the video surveillance market is valued at $ 53.7. And with the advent of AI technology, the market is set to grow at a CAGR of 9.2% by 2028.

Computer vision AI has revolutionized video surveillance by making security operations, disaster management, and risk mitigation more streamlined and robust.

Ready to Take Your Video Surveillance to the Next Level with Computer Vision?

From deterring crimes to improving customer experience, the benefits of AI-enabled video surveillance are endless. If you haven’t adopted computer vision surveillance, now is the time.

Contact Einfonets Technologies to learn more about computer and embedded vision technology solutions.

We are a leading computer vision company that helps you make your video surveillance more practical, meticulous, and AI-powered. We have a team of experts who have extensive experience and expertise in developing scalable, cost-effective, and customized computer vision projects.

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