Video Analytics In CCTV

According to Allied Market Research,  the video analytics market size is projected to reach $20.80 billion by 2027, growing at a CAGR of 22.7% from 2020 to 2027. While Video Analytics is one of the most trending topic in the world of surveillance technology, there is a need to understand what are the different areas in which it can be applied and how different enterprises can make use of it. In this blog, we share the basics of Video Analytics, along with its application and key players in the market.

What is Video Analytics in CCTV

Video analytics is a technology that helps analyze and review surveillance videos such that any useful incidents could be found out and hence making surveillance system more efficient and useful. It also reduces the workload on security and management staff. There are three common types of video analytics:
             • Fixed algorithm analytics
             • Artificial intelligence learning algorithms
             • Facial recognition systems
The first two of these determine if an unwanted or suspicious behavior is occurring in the field of view of a video camera and the algorithm notifies the finding. However, each takes a different route to get to its result. Fixed algorithm analytics use an algorithm that is designed to perform a specific task and look for a specific behavior. In comparison, Artificial intelligence learning algorithms come as a blank slate. After connecting to a given camera, they begin to learn and then start issuing alerts and alarms after several weeks.

  Example behaviors of fixed algorithm analytics :

            • Crossing a line
            • Moving in the wrong direction down a corridor
            • Leaving an article
            • Picking up an article
            • Loitering
            • Floating face down in a swimming pool

Example of Artificial intelligence learning algorithms :

Learning the human patterns at an airport arrival terminal and create alarms accordingly. This type of analytics differs based on location, time, etc. For example alarms at the airport terminals in India will be different from alarms at the airport terminals in Singapore.

Facial recognition Systems :

Facial recognition systems are used for access control or to help identify human. Typical facial recognition systems match points on a face with a sample stored in a database. The latest version of facial recognition systems constructs 3-D maps of faces in real time and compares those to a truly vast database, as vast as country-sized database of images (millions of records).  More information regarding facial recognition system can be found in my blog here.

5 Key Functions of Video Analytics in CCTV

Intelligent Motion Detection

Video analytics software is based on various algorithms that will analyse the CCTV footage to determine the type of motion that can be of a person or vehicle. For a person, it further allows definition of a virtual line beyond which any kind of human trespassing can be alarmed. Moving in wrong direction, loitering can also be caught using intelligent motion detection. Occupancy estimation is another interesting behavior that helps determine how many people are present at a particular location of the venue. People counting helps in counting the number of people passing or exiting the area.

Object Recognition

Video analytics within a CCTV system helps define an area of control within which one can monitor for missing or abandoned objects.

Number Plate Recognition

This system allows the camera to detect automobile licence plates that can then be integrated in the system for behaviour monitoring. It also allows cameras within the CCTV system to determine the direction the vehicles are heading towards.

Heat Mapping

This feature uses recoloring mechanism by which it determines the motion in a particular area. Understanding the motion flow helps determine the area in which there is the most crowd or movement. We can also gain information regarding the days and times of the day when the crowd is more. This feature would help owners in making calculated decisions for product sales and personnel allocation. Like most heat mapping software applications, the areas of highest traffic are displayed in Red and Lowest in Blue.

Auto-tracking Motion

Video analytics can also be coupled with pan/tilt/zoom (PTZ) cameras within a CCTV system, which enables auto-tracking capabilities or real-time tracking.

While the industry is still exploring and weighing its potential, more functions and features are being introduced in these systems. These include smoke detection, behavioral analysis, features for military applications, forensic studies and 3D volumetric analysis.

Components of Video Analytics

Hardware source that streams the video : The data being analysed can come from various streaming video sources. The most common are CCTV cameras, traffic cameras and online video feeds. However, any video source that uses the appropriate protocol (e.g. RTSP: real-time streaming protocol or HTTP) can generally be integrated into the solution. A key goal is coverage: we need to have a clear view of the entire area, and from various angles, where the events being monitored might occur. More the data, better the processing.


Video analysis software that processes the data : Video analysis software can be run centrally on servers that are generally located in the monitoring station, which is known as central processing. Or, it can be embedded in the cameras themselves, known as edge processing. The third one is a hybrid approach, where partial processing performed by the cameras and then passed to central server for further processing. This approach reduces the data being processed by the central servers, which otherwise could require extensive processing capabilities and bandwidth as the number of cameras increases. In addition, it is possible to configure the software to only send data about suspicious events to the server over the network, reducing network traffic and the need for storage.

Applications of Video Analytics


Key Players of Video Analytics

While there are many brands that provide video analytics capabilities, below are the few brands which we have studied and what is the prominent video analytics function they perform. Also, most of the brands provide hardware as well as software, there are few who provide only the software. These software brands make sure that they are compatible with topmost hardware brands available in the market.
Siemens provided highly automated wide-area video analytics software, capable of features like intelligent alarm monitoring and interactive event response and Perimeter intrusion detection.
Axis Communications recently introduced a new chip, the ARTPEC-4, which enhances the image quality and video analytics performance in Axis’ network video cameras and video encoders. It is designed to offer video with lower noise and higher light sensitivity for sharper images of moving objects. With a powerful CPU and a co-processor for accelerating video analytics, ARTPEC-4 also has more processing power for intelligent video analysis.
Bosch video analytics is embedded in cameras, making it convenient and efficient. Bosch IVA performs multi-level image analysis of pixels, textures and motion content, from inside the camera.
Hikvisions Central Management System includes software as well as hardware includes advanced Event and Alarm management features (Video Analytics, POS, and more).
Dahuas 256CH Intelligent Video Surveillance Server is an all-in-one Artificial Intelligence server with advanced deep learning algorithms perform powerful video structure analysis to achieve precision human facial analysis, entrance/exit management, where knowing who is coming and going is a valuable asset. I
Honeywell’s video analytics suite analyses the behaviour of individuals and vehicles to provide real-time alarms and search tools that enhance manned and unmanned video surveillance systems.

                    Click here for  a Sample Video Analytics from Dahua 

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