Computer vision shows the way

Retail is one of the industries that benefits most from computer vision applications. The solutions are numerous, diverse and clearly make a difference to customers and business processes.

Computer vision is able to take the customer experience in retail to the next level – for example, through the recognition of facial expressions and emotions, through automatic notifications of staff to replenish empty shelves or even through personalised customer greetings. The revolutionary solutions also include the ‘try-before-you-buy’ service, which makes it possible to virtually ‘place’ furniture in a room or to ‘try on’ shoes and cosmetics via the smartphone camera. In addition, desired products can be found by means of reverse image searching. Optimised product matching and AI-generated recommendations ensure individual style advice.

Real-time analysis of videos from surveillance cameras can also help to attain a higher level of security: Thus, modern computer vision applications can not only quickly identify criminals or people making a run for it and trigger a corresponding alarm, but they can also detect customers with suspicious behaviour at an early stage through motion analysis. This results in rapid theft detection or even makes it possible completely prevent theft by being alerted in a timely manner. Security staff are automatically informed to resolve the respective situation quickly and discreetly.

With the help of computer vision, time-consuming diagnostic activities can be automated so that specialists can concentrate on devising treatment plans and communicating with patients. The applications provide diagnostic aids in areas such as radiology, oncology, cardiology and dermatology, facilitate laboratory tests and assist with surgery and physiotherapy. Benefits include early disease detection, more accurate measurements, increased efficiency, image interactivity and 3D visualisations, as well as automatic report generation based on extracted data. In addition, computer vision can be used to make diagnoses in places where there is a shortage of specialists, such as poorer countries and smaller cities around the world.

With the help of modern computer vision applications, agriculture can also be made more efficient, resource saving and environmentally friendly. In arable farming, for example, remote sensing is used to create application maps from satellite images, which are used for the targeted application of fertiliser. During the harvest, farmers are actively supported by their combine harvesters, which automatically detect the grain size and optimise the machine settings accordingly.

In livestock farming, computer vision applications can be used to automatically count and track livestock. In this way, herd behaviour can be monitored, allowing farmers to respond to any deviations from the norm at an early stage. In the barn, the health status of animals can be determined by analysing their posture.

Lengthy and paper-heavy procedures still exist in the insurance industry today. Filing a claim can be a tedious process for both insurers and their customers, and the former also have to constantly keep an eye out for and identify fraud attempts. Through modern computer vision applications, we can not only simplify compensation processes, but also accelerate them tremendously. With digital claims management, users submit their claims fully digitally, for example by uploading photos of a damaged vehicle. The application can identify the extent of the damage on the images and determine the costs required for repair. Such a solution leads to lower processing costs, more accurate estimates and higher customer satisfaction.

Sport is an important part of our culture. But while practically every major league match is televised, camera crews are rarely found when local teams face off. This is where computer vision enters the picture. With systems that control cameras fully automatically, any match can be streamed effortlessly on the Internet. Learn more in our use case for soccerwatch.tv.

In addition, it is possible to analyse matches with more precision, evaluate referee decisions and measure player performance. For coaches, this represents a highly valuable advantage. Of course, this application can not only be applied to football, but to any sport.