The large volume of video data captured by the ever increasing number of moving cameras and surveillance cameras is posing new challenges for video analytics. Videos are uploaded and recorded day by day using device like mobile phone, security surveillance and camera in mall. Especially, more than 100TB data are recorded in a world in a day. Mostly recorded video data is in unstructured format and in unconstrained environment. Hence there is an intense need to process this huge video data.
Video content analysis (also Video content analytics) is the process of automatically analysing video to detect and determine temporal and spatial events. It is also referred to as video analytics in short.
To find unique information from large video is a big and unique challenge. Video analytic represent automatically discovered pattern and find correlation present in large volume of video data. By using new Computer vision technology we have the ability to mine valuable data about what‘s happening in the real world. Which can help the end-user to take informed and intelligent decisions as well as predict the future based on the patterns discovered across space and time?
There are method which works on advance object detection, classification, tracking and semantic representation of large volume of big video data. This method defines a number of concepts and their relations, which allows users to use them to annotate related events. These methods falls under computer vision category.
Video analytic application ranging from Behaviors analysis of person and animal, Retail market analysis, Intelligent Vehicle System, health-care and life science, traffic Management and so on. We are moving towards the era where automated video analytics will be applicable for real-life, real-time critical applications. Few application are briefly explained below:
Applications of Video Analytics
Intelligent vehicle system
Intelligent vehicle system consists of various applications such as intelligent parking, travel time prediction, incident prediction, pedestrian and cyclist detection, automated traffic sign detection, etc.
Video analytic in Retail market
Retailers are interested in learning customer behaviour patterns using the already set-up visual surveillance systems for security in the store. Customer behaviour understanding has an impact on various business analytics solutions including increase in sales and decrease in customer related frauds. Dwell time analysis also helps in understanding which products are more popular than other.
Health-care and Life Sciences
Behaviour analysis, unusual activity detection, facial expression detection and recognition are well-suited for monitoring patients and elderly people in hospitals and smart homes. Monitoring old people living alone helps ensure their safety and security while also keeping a track on their health. Automated fall detection using video analytics is necessary to bring help to patients and elderly who live alone and are especially useful in cases where the people cannot call for help because of becoming immobile or unconscious.
Intelligent traffic management is another important area where video analytics finds application. It helps in learning the patterns of traffic flows across the cities, and helps in traffic planning and management. License plate recognition helps in automatic toll collection, efficient vehicle surveillance and effective law enforcement. Analytics of traffic videos help in congestion control and traffic light management.
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