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What is On-site Video Analytics and How Does it Work?

So much more than video management

Like it or not, the world is becoming more and more digital. Therefore, more and more data is being captured and stored each day. Real-time video analytics solutions help us make sense of all this data.

Traditional video surveillance systems are not enough. Police departments are starting to use in-camera video analytics to help with crime prevention, retail businesses are using video analytics to reduce theft, and city councils are using video analytics to improve traffic flow. The possibilities are endless.

Keep reading to learn more about the different types of video analytics, their various benefits to your organization, and real-world applications of video analytics for government facilities, retail businesses, healthcare facilities, and more.

A brief history of video analytics

Video Analytics Street Camera

The use of video analytics started in the early 1980s and 1990s in manufacturing and has evolved to include various new functionalities. While video analytics changed our lives, this technology is still very new. So let's explore how it all began, changes to these systems in the past few decades, and expectations for future development.

Up until the early 1980s, video analytics were primarily used for manufacturing. But as technology improved and prices fell, it became easier to use this type of system from a business perspective. In the 1990s, video surveillance systems became popular. Around this time, software developers introduced machine-vision algorithms into these systems to detect objects and people.

Video analytics and market research

In the 2000s, marketers started using video analytics solutions for consumer research and trend forecasting. Since then, detecting a person's gender, age, and even emotional state has become possible. More and more companies began to use this technology to create targeted advertisements and customer segmentation. For example, Facebook now offers advertisers a way to send customized ads based on the age and gender of the user.

Let's look at some types of video analytics systems to help you better understand their capabilities.

Briefcam video analytics

How does video analysis work?

Video analytics refers to the process of automatically extracting information from video footage. Organizations can use this information for various purposes such as crime prevention, traffic management, and marketing research.

Based on the book "Effective Physical Security" by Thomas L. Norman CPP, PSP, CSC. There are three types of video algorithms in video analytics solutions:

  • Fixed algorithm analytics

  • Artificial intelligence learning algorithms

  • Facial recognition systems

Fixed algorithm analytics

The first two of these strategies attempt to accomplish the same thing. They try to determine whether an undesirable or suspicious activity occurs in the video camera's field of view and notify the console operator of the occurrence. Each, however, follows a distinct path to arrive at its conclusion. For example, fixed algorithm analytics employ a pre-programmed algorithm that does not change unless a security system administrator or engineer changes the program itself.

A.I. algorithms

Artificial intelligence learning algorithms, on the other hand, are adaptive, which means that they automatically learn from their environment within specific parameters set by their developers. Therefore, these solutions become more accurate at detecting suspicious activity over time for system administrators.

Hanwha Street Cameras

Facial Recognition

Facial recognition systems, the third approach to video analytics, are also adaptive. But unlike other forms of intelligent video analysis software, they utilize specific computer vision techniques to compare images within the camera's field of view with known photographs or videos that have been tagged as potential threats. And just like the first two types of video algorithms, this type of technology is also pre-programmed to look for specific individuals or objects.

What types of businesses use video analytics?

Intelligent video analysis may be helpful in unexpected sectors, such as retail, helping companies better understand consumers by analyzing their behavior in stores. Additionally, businesses can monitor consumer behavior such as gaze patterns, visit durations, and sales site locations. For example, they can show where customers cluster in the store or when they pick up a product and then put it back down again. Through this technology, retail businesses can improve their store layouts and displays to encourage customers to browse items more thoroughly.

Video analytics in healthcare

Video surveillance is used in many healthcare organizations to monitor their facilities. Integrating video content analytics technologies may help them maximize their video surveillance investments, enhance security, and improve operational efficiency. By increasing situational awareness and optimizing traffic flows, hospitals and nursing homes can run more efficiently while keeping patients and staff safe.

More industries that benefit from video analytics

Facial recognition software may be helpful on dating sites where users can upload a profile picture. This way, users can find out if their prospective mate is a serial dater or if they have been married before.

Some financial institutions also use the technology to allow customers to deposit checks with video security systems that analyze their behavior as they complete the transaction.

Edge-based analytics

Edge-based video analytics work on the edge devices such as cameras. As a result, edge-based video analytics have several advantages over server-based video analytics:

  1. Edge devices are always on and can process data locally, reducing the server's load and improving performance.

  2. Edge devices can make decisions based on local data, reducing latency and increasing accuracy.

  3. Edge devices can act as redundant storage for data, ensuring that data remains safe in case of a server failure.

  4. Edge devices can filter out irrelevant data.

Briefcam analytics

Server-based analytics

Briefcam edge analytics

There are several advantages of server-based video analytics over edge-based video analytics:

  1. Server-based video analytics can process much more data than edge-based video analytics, which allows for more accurate analysis.

  2. Server-based video analytics can correlate data from multiple cameras, which increases the accuracy of the analysis.

  3. Server-based video analytics can use artificial intelligence and machine learning to improve its accuracy over time.

  4. Server-based video analytics can store data for extended periods, allowing longer-term analysis.

  5. Using Server-based video analytics, you can create dashboards and reports that provide a detailed overview of the data collected by the system.

What is metadata tagging?

Video content analysis metadata tagging automatically generates data tags that describe what the system detects in a scene. This data can be anything from the weather, date, time, or who is in the video feed. Video analytics metadata tags are automatically generated and do not require manual input from the user. Users can configure the tags but cannot directly edit them by hand. Upon creating a label, it remains in the video feed, permanently associated with that piece of footage. Metadata tagging, therefore, eliminates the need for security personnel to sort through videos manually.

Advantages of metadata tagging

The main advantage of using metadata tagging is that it allows you to view information about an event at a glance instead of viewing the entire video footage. For example, suppose a traffic video feed undergoes metadata tagging. In that case, security personnel can quickly see how many vehicles were captured by the camera and what time they moved through the area. Without metadata tagging, an average viewer would have to watch several minutes' worth of footage to obtain this information.

Typical Applications for Video Analytics Solutions

Indoor people tracking is tracking the movement of people inside a building. For example, it can track the activity of employees in a corporate office, patients in a hospital, or students in a school. Indoor people tracking can track everything from the location of people to the direction they are moving in, and the time they spend in different areas of the building.

Indoor People Tracking

The main advantage of indoor people tracking is that it gathers data in real-time, enabling you to respond quickly to changes in the environment. For example, suppose you are following the walking direction of people in a building or airport at any given time and notice someone walking against the directed traffic flow. The system provides an alert, directing you to this potentially dangerous situation.

Outdoor People & Vehicle Tracking

The outdoor environment is often challenging to monitor, but this doesn't mean video analytics don't apply as a surveillance tool in this instance. Outdoor People and Vehicle Tracking systems use advanced video analytics for tracking the movement of vehicles or people in your parking lot - perfect if you want peace of mind that somebody isn't driving around without supervision. Even when faced with poor weather conditions like rain, the system also has high accuracy because its sensors can keep working despite limited visibility.

Traffic Monitoring

Traffic monitoring systems use video analytics solutions to monitor traffic intersections, toll booths, construction zones, parking lots, traffic light control systems, and other areas where vehicles are constantly moving. The system can automatically identify individual vehicles by license plate or model. Vehicles passing through the system will be associated with a timestamp that records latitude and longitude. In addition, the data can measure traffic flow and generate reports that indicate the average speed of vehicles traveling in a specific area.

Axis Communications traffic Monitoring
Axis Communications

Human Behavior Analysis

The system can automatically identify individual people based on their look, clothing, gait, or way of walking. Behavior analysis systems use algorithms to distinguish between people and objects by analyzing an object's shape, color, height, width, texture, and motion. For example, a behavior analysis system can monitor a retail store or a public space for potential theft, security breaches, or marketing purposes. Video content analysis can also automatically generate heat maps that indicate potential areas of interest to the watcher. These heat maps are ideal for analyzing which areas were identified as interesting by an individual or group.

Briefcam video

Crowd Detection

Crowd detection is the process of using video analytics solutions to identify and track large groups of people in a scene. Video analytics software can determine how many individuals might be found in one area and trigger an alert when the number is exceeded (capacity). For security or service quality purposes, crowd detection is perfect for detecting substantial groups of people.

The main advantage of using a video analytics solution for crowd detection is that it provides real-time updates on location and movement, allowing security personnel to respond quickly to changes in the environment. For example, suppose a large group of people gathers at an entrance to a building. In that case, security personnel can be alerted to prevent the crowd from entering the building.

Face Recognition

Face recognition is a video analytics solution that processes video feeds to identify and track individuals in a scene by their facial features. The software allows security personnel to identify individuals who may be involved in a crime quickly. The main advantage of using video analytics for face recognition is that it can provide real-time updates on the location and movement of an individual. For example, suppose an individual is spotted on camera carrying a handbag taken from a store without paying for it. In that case, security personnel can watch as the individual moves through the building and be alerted as soon as they leave.

Reduce identity fraud

Face recognition safe-lists and deny-lists are a great way to manage the people who can access certain areas. For example, suppose you have a restricted area in your office. In that case, you can use face recognition software to create a safe-list of the employees who can access the site. Then, if someone not on the safe-list attempts to access the area, they will be denied access.

Using safe-lists and deny-lists can cut down on identity fraud. It allows you to only provide the necessary information to the people allowed unrestricted access, thus minimizing the chances of third parties obtaining your data for fraudulent purposes. The standard method of building a face recognition safe-list or deny-list is to use video analytics software to capture facial features and match them with those already in your database. This process allows you to quickly build a safe-list or deny-list of authorized people for different areas.

Left & removed object detection

Object detection captures changes in the appearance and disappearance of stationary objects in a specific area. This type of detection is often used in airports and underground systems, identifying blocked fire escapes or possible bomb threats.

Object detection ensures all objects are detected and can provide alerts when this is not the case while also providing alerts for unusual objects in the visibility field. For example, suppose someone leaves an unattended bag under a bench in a public space. In that case, you can receive an alert so that someone can check the bag and see if it contains anything dangerous.

Loitering detection

Video analytics loitering detection is the process of using video analytics to identify and track individuals who are loitering in a scene. For example, suppose an individual is spotted on a video camera hanging around a building for no apparent reason. In that case, security personnel can be alerted to investigate.

Applications of video analytics loitering detection

A typical application of video analytics loitering detection is the prevention of shoplifting. For example, suppose a system identifies a loiterer outside a store as someone who has previously committed theft or theft-related offenses. Security personnel can then be alerted to investigate and watch for suspicious behavior. Video analytics loitering detection can also be helpful in locations with a high-security threat, such as airports or prisons. These locations contain restricted areas, and loitering detection can alert you to a successful breach.

People counting

Video analytics people counting is the process of using video analytics to count the number of people who are in a scene. This information helps organizations track people's movement and understand traffic flow in a location. The main advantage of using video analytics for people counting is that it can provide real-time updates on the number of people in a scene. For example, suppose the number of people in a location suddenly increases. In that case, security personnel can be alerted to investigate.

Another common application of video analytics people counting is in retail stores. By understanding traffic flow, stores can optimize their layout to improve customer satisfaction. For example, stores often implement specific promotional campaigns around holidays or other perceived peak times. Video analytics people counting can make these campaigns more accurate by tracking the flow of traffic throughout the day, allowing them to plan their promotional activities during peak periods when there is likely to be most interest in their products or services.

Vehicle recognition is the process of identifying a vehicle based on its characteristics. Video analytics solutions accomplish this by using video of the cars. Once a car is recognized, the system captures its attributes in a database, facilitating the tracking of vehicles over time.

Automatic license plate recognition (ALPR) is a subset of vehicle recognition that focuses specifically on identifying license plates. ALPR systems use CCTV cameras to capture images of license plates. These images are then processed to extract the license plate number. The extracted license plate number is stored and then compared to a database of known license plates. If the system finds a match, it retrieves the associated information (such as the vehicle owner)from the database.

The main advantage of using ALPR is that it can provide accurate information about the movement of vehicles over time, allowing for the tracking of vehicles over time, which helps to understand traffic patterns and identify suspects in criminal investigations. Here are some of the most common questions that people ask about video analytics:

Automatic license plate & vehicle recognition

License Plate Recognition

What is the difference between video analytics and video surveillance?

Video analytics is the process of using software to analyze video footage to extract information. For example, a video surveillance system or CCTV is a group of video surveillance cameras used to capture footage for security purposes.

The main difference between video analytics and video surveillance is that video analytics uses software to analyze the footage to extract information. In contrast, video surveillance simply captures footage through a system of cameras for security purposes. Video analytics has various applications such as people-counting, loitering detection, and vehicle recognition. In comparison, CCTV applies primarily to security scenarios, such as capturing footage of criminal activity.

How does video analytics work?

Video analytics works by using software to analyze video footage and extract information. In addition, video analytics can use different algorithms to detect and track objects in the footage.

What are some of the applications of video analytics?

Video analytics has many different uses. Some of the most common applications are security, marketing, and transportation, with the security industry being one of the largest service areas. Video analytics can help identify and track suspicious activity, keeping people safe and secure.

Marketers can also use video analytics to track how people react to their videos. Therefore, they can improve their marketing campaigns and obtain better results by monitoring reactions.

Transportation agencies can use video analytics to improve their operations. For example, they can use video analytics to track traffic flow and optimize their routes.

What are the benefits of using video analytics?

Video analytics can provide organizations with a variety of benefits, including the following:

  • Enhanced security: By tracking the movement of people and vehicles in and around your premises, video analytics can help you detect and prevent unauthorized access or theft.

  • Improved efficiency: Video analytics can help organizations optimize their operations by identifying areas to improve processes or limit wasted resources.

  • Better customer service: By analyzing footage of customer interactions, video analytics can help businesses understand what customers are looking for and how to improve service.