by Michal Miernik
For some time now, CCTV camera systems have not been just an image on screen observed by a security guard in a building. The development of AI technology and the Internet has made CCTV a powerful tool not only providing security, but also allowing better sales and business management. How to use artificial intelligence to process camera images?
The main task of CCTV is to catch such events as theft, burglary or assault, so it quickly found its way to shopping centers, shops, office buildings or hotels. Camera systems, which are used to ensure people’s safety, are now also widely used on the streets, as they enable the authorities to find the perpetrator of an accident or a terrorist attack.
Existing since the 1970s the camera systems allow to track events inside and outside the building at one moment. The image is transmitted to the center – usually the security headquarters in the facility, where the staff can watch what is happening on the monitors. Initially, the systems were analog and the image was recorded on VHS tapes. With the development of technology, CCTV systems began to use e.g. time lapse or switch on reacting to movement. Today, thanks to the Internet and high definition technology, CCTV is much more efficient. The digital image is stored on servers, offers much better quality and allows for better analysis.
In recent years, the increasingly rapid development of artificial intelligence has led to this technology also being used for image analysis. Static images such as pictures or graphics are no longer a problem for learning algorithms. It was a bit different in the case of video, because the challenge is to quickly analyze all the frames in the film. Both increasingly powerful hardware and „smarter” algorithms come in handy. The accurate analysis of the image has been made possible by Deep Learning – a part of a family of machine learning methods based on artificial neural networks. Deep Learning is able to learn on its own from unstructured data such as image and sound. Currently, solutions such as CX Metrics are able to analyze video in real time from multiple cameras at once. This makes it possible, for example, to track a person and build a behavioral profile.
As I mentioned earlier, today’s CCTV, thanks to digital transmission, allows for accurate image analysis. It is of a much better quality, so you can recognize many features and get a hold of different behaviors from the observed crowd. For example, the camera in the shop is able to recognize gender, age, facial features, silhouettes, and even clothing characteristics. Add to that the ability to count people entering and leaving and you have a powerful marketing tool.
Once the system has the ability to recognize numerous features, the retailer can build marketing scenarios that may improve customer experience and thus increase shop turnover. Here are some of the scenarios that will help you run your business efficiently:
These are just some of the scenarios that the store can implement to improve sales. The flexibility of tools and algorithms allows to build dedicated and more intricate solutions. Systems such as CX Metrics can also be helpful in researching customer preferences or analyzing store security levels. In the following articles we will show different applications of computer vision on our example. If you would like to be up to date with the latest technologies using artificial intelligence in the retail industry, subscribe to our blog.