Video Analytics has come a long way from being a security solution to providing insights to manage traffic, determine store layout, facial recognition, smart parking and remote medical care. Today, video analytics is a big deal because the real time video streams can help deliver business insights automatically, previously considered manual.
The adoption of IoT, machine learning algorithms, artificial intelligence, smart devices, and robotics are playing an important role in transforming the businesses and develop interesting use cases across industries.
Video analytics or content analysis (also video content analytics, VCA) is the capability of automatically analyzing video to detect and determine temporal and spatial events. Video Motion Detection is one of the simpler forms where motion is detected regarding a fixed background scene. Video analytics is used for real time analytics, post event video management system (VMS) forensics, and on-demand analytics using the cloud.
TYPES OF VIDEO ANALYTICS
Fixed algorithm analytics
Fixed algorithm analytics uses an algorithm that is designed to perform a specific task and look for a specific behaviour. E.g. moving in the wrong direction, crossing a line, loitering, etc. Fixed algorithms are looking for a specific behaviour.
Artificial Intelligence Learning Algorithms
Artificial intelligence Learning algorithm systems begin as a blank slate. It is connected to the cameras and it will start recording data for weeks as the system is learning what is good and report the inconsistencies.
Facial Recognition Systems
Facial Recognition System is used to recognize the face and match it with a database. This system can allow people to enter a building with face recognition or match a person with a criminal record in the database.
COMMON VIDEO ANALYTICS
The algorithms are written to detect motion, but you can also write algorithms be to detect specific behaviors within the scene view of the video camera. Common video analytics include:
• Picking up of an article
• Leaving an article
• An object placed in the scene and left behind
• Detection of Loitering
• A person or object entering from the wrong direction
• Person, vehicle, or object stopping
• Fence trespassing detection
• Detection of moving object, person or vehicle for autonomous vehicles
HOW DOES VIDEO ANALYTICS WORK
• The analytics algorithm searches for and captures relevant bits of information.
• This information is examined and categorized based on the trend identified.
• The information analyzed is turned into actionable insights.
• The recommended actions, along with supporting information, are transmitted to the surveillance systems or people monitoring them
• This helps systems and authorities in identifying security breach patterns and preventing them.
WHY VIDEO ANALYTICS
Video analytics used to be a privilege service enjoyed by government agencies and corporates as it needed powerful servers and huge bandwidth. However, because of increase in demand, development of new platforms, usage of AI, deep learning and matured systems, it is widely available and anyone can use video analytics today.
Video analytics takes care of real time video streams to deliver business insights automatically previously considered manual.
Video analytics has been growing at a rapid pace in many verticals. The growth of video analytics market, maturity of systems, and affordability of compute power has made it affordable and accessible by many.
The usage of artificial intelligence and deep learning has made video analytics a force to reckon with and provide useful insights to manage traffic, make factories safer, make cities smarter, and make car smarter.
The insights derived from the video analytics systems are helping organizations make better decisions to improve customer experience, change the layout of the store, catch a suspicious activity, provide safety, save lives and much more.
THE GAME CHANGER
Traditionally, businesses and apartment complexes have been using video surveillance so their security personnel can watch the feed and catch a suspicious activity. But the software applications today can monitor the feed round the clock, and can raise alert based on different parameters.
In recent years, video analytics has become an essential part of a wide range of use cases. Use of machine learning and deep learning approaches have triggered a huge growth in video analytics market making it a game changer for smart cities, transportation, automotive, healthcare, retail and security verticals.
Rising concerns for safety and security of the public and for reducing the crime rates through time alerts about any unusual activities is projected to boost the market growth in the forthcoming years.
The demand for intelligent video surveillance is also expected to increase owing to the surplus features associated which include enhanced reliability, improved accuracy, and cost effectiveness along with its rising application in business intelligence. The software is majorly used for gaining insights on various patterns with respect to traffic movement, consumer behaviour, and frequency of footfall at a defined area.
Crowd monitoring and people count application segment of video analytics is projected to contribute majorly to the market growth over the forecast period. The application of video analytics in crowd management include identification of dominant patterns of the crowd, crowd size estimation, and determines suspicious activities among the crowd.
The Video Analytics & Intelligent Video Surveillance Market reached USD 28.13 Billion in 2018 and is expected to attain a market value of USD 103.83 Billion by the end of 2027 by registering a CAGR of 15.14% (2019-2027) across the globe. (Source – ResearchAndMarkets.com)
SecurityVideo Surveillance has been used for providing security at homes, offices, and commercial establishments for ages. Video Analytics plays an important role in identifying people through facial recognition in real-time and identifying if there is any suspicious activity. The algorithms are trained to find if there is a change in pattern, if a person leaves a bag and walks out, if someone enters a restricted area or if someone is found stealing.
Security is a universal requirement for homes, offices, and commercial establishments. But video analytics has made it possible to develop use cases beyond video surveillance and monitoring.
Video analytics plays an important role in the smooth functioning of traffic, solving crimes and providing important insights about the type of vehicles, counting vehicles and license plate recognition.
The software can warn if a vehicle has entered from the wrong side, identify a suspicious movement, help discover the cause of accident, vehicle tracking and the data captured through various cameras can help reduce accidents and manage traffic better.
Healthcare industry and institutions have been using video surveillance to provide security for their premises and monitor the movement of visitors, staff and patients for a long time. Video surveillance is useful to keep patients’ records safe, prevents intruders to gain access to restricted areas, ensure staff are meeting safety and health standards, prevents abduction of infants and stealing medicines.
Now healthcare institutions can use video analytics solutions to increase efficiency of serving patients, faster check-out times, maintain health standards and manage patients remotely with the help of surveillance, smart phones and wearable devices.
Surveillance solutions have been popular in the retail segment to catch shop lifters and keep the robbers away. However, video analytics and machine language have created various opportunities to study the behaviour of people visiting the store, determine their characteristics, and demographics to determine the right display and product strategy for the store.
Video Analytics can help figure out if it is a repeat customer, how many people visited the store, how much time did they spend at each spot, analyze their behaviour and buying patterns. This data helps in optimizing promotions and product displays to provide better customer experience and increase in revenue.
Automated Vehicle detection and classification is an important component of intelligent transport system. Video Analytics and the real-time data play an important role in traffic accidents avoidance, toll collection, congestion avoidance, terrorist activities monitoring, security and surveillance systems.
Video Analytics is key and essential to management of logistics, routing, autonomous (self-driving) vehicles and navigation.
Video Analytics used to be a luxury and accessible by a few, but not anymore. The advancements in technology, cheaper hardware, and a wide variety of use cases has made video analytics a popular choice for providing insights to not only provide surveillance but also make important decisions to grow business.
Even though security, retail, healthcare, and transportation industries represent perfect use cases for video analytics, there are many new use cases developing in other verticals. The usage of machine learning and deep learning has taken video analytics to a new level. The Video Analytics & Intelligent Video Surveillance Market reached USD 28.13 Billion in 2018 and is expected to attain a market value of USD 103.83 Billion by the end of 2027 by registering a CAGR of 15.14% (2019-2027) across the globe. (Source – ResearchAndMarkets.com)
We at Inference Labs have vast experience and trained data scientists to provide a customized video analytics solution for each use case and help our customers find better insights and grow revenue. We will be happy to review your business and suggest a solution.
If you have questions, please reach out to me: firstname.lastname@example.org
Sumit Arora is Chief Revenue Officer at Inference Labs