Video surveillance and video analytics

Video Analytics was invented with a motive – to help in reviewing the growing hours of surveillance video that a security guard or a system manager (or a human) may never have time to watch. Video Surveillance systems equipped with Video Analytics can help us in finding those minor details that can’t be perceived by naked eyes. Video Analytics or Video Content Analysis is computerized video footage analysis that uses algorithms to differentiate between object types and identify specific behavior or action in real-time, providing alerts and insights to users. Since Video Analytics is based on the technology of Artificial Intelligence, experience plays a significant role. A highly trained model can see through very minute details in video footage.

This technical capability is being used in a wide range of domains, including entertainment, health-care, retail, transport, home automation, flame, and smoke detection, safety, and security.

Video Analytics relies on useful video input. To make the video useful, following techniques are implemented for increasing the quality of the video recorded:
1. Video Denoising
2. Image Stabilisation
3. Unsharp Masking
4. Super-Resolution

What are the Commercial Applications of Video Analytics?

CCTV Systems – This is the most widespread application of Video Analytics. VCA(Video Content Analysis) is distributed on the cameras (at the edge) or centralized on dedicated processing systems. These CCTV’s, for example, can be used to detect and report any suspicious activities of shoppers in a store. Another popular example, is the PIDS(Perimeter Intrusion Detection System). It is deployed in areas whose perimeter can extend to a large radius, like airports, seaports, and the railways. With this technology, we are able to track any intrusions in real-time, giving us sufficient time to react.

  • Traffic Systems – Deployment of Video Analytics on busy squares in crowded cities of the world can be a massive time-saver for the people and the government. At peak times of the day, when the traffic is very high, specialized use of analytics can be used to avoid congestion.


  • Counter-Flow Detection – Walking against the flow in specific locations, such as the airport security checkpoint and gates, can be a sign of some danger. It can potentially result in terminal shutdowns. The wrong entry of vehicles in a one-way can lead to congestion affecting a large number of people. These faults can be quickly responded to by the uses of video Analytics.
  • Suspect Search – The data of facial-recognition can be aggregated along with video Analytics for the detection of criminals at high-security places like the airports’ immigration counter, the baggage collection facility, taxi stands, etc. This can lead to the smooth and swift arrest of such people or elimination of such objects. Time is the essence when looking for something critical.


  • Long Queue Problems at the Shopping Centres – In the densely populated countries like China, India, the crowd increases significantly in stores during the festive season. Trends in data can be used to analyze the crowd and arrange for particular changes for a short duration of time, increasing the store efficiency, and saving the time of the people.
  • Reducing Retail Shrinkage – Retail and logistics companies can use video surveillance analytics to minimize inventory loss significantly. The model is trained to detect unusual activities like unexpected times of presence, unauthorized access, or any suspicious movement of inventory and more.


  • Improving Patient Satisfaction – Video analytics can help hospitals and dispensaries to improve the overall patient experience. Artificially engineered cameras can continuously monitor patients waiting to meet the doctor and ensure they are checked-in within a given time duration. Even an alert can be sent to the staff regarding a patient who has been left unattended for a long time.

Video Analytics is the smart way of engaging customers, reducing wastage of time and improve security. Video data collected is massive and it would be practically impossible for a human to replace a computer. With the fast pace of life and the amount of video content today, using video analytics is a lifesaver for different fields.