What is Computer Vision?

What is Computer Vision?

Computer vision is a field of artificial intelligence, which is nowadays in the center of attention. It’s related to image and video analysis. There is a set of special techniques. They are actively used in order to empower the computer to extract that information, which is of the highest importance.

There is usually a photo or video camera in the system. As for the specialized software, it’s also in the center of attention. it can be used to  identify and classify the objects. This way is rather important for analysis of the images. And faces and emotions are also here.

Machine learning technologies are created to teach a computer to find important information. It includes the collection of big volume of data. Such approach allows you to isolate features and combinations of features. They are used for further identification of similar objects of artificial intelligence development company – Unicsoft.

Why does a business need computer vision?

• Access control systems is based on face recognition. They are applicable in almost all areas: there are business centers and company offices to banks and restaurants.
• There is quick identification by face. In such a way can be shortened the time of customer service and offer personalized services.
• Strengthening human capabilities. Computer vision allows you to see what a person might not notice. This is especially true in medicine (analysis of X-rays and other images) and industry (detection of defects).
• Reduced time for routine tasks. It usually takes just a few seconds to make the recognition. And in case if there is need to examine a shelf for the incorrect display, it will take much longer for a person.
• It’s impossible to develop unmanned vehicles and robots if not to use computer vision.

What is the problem?

For the further spread of computer vision systems in the business environment, developers are solving the problem of speed and stability of systems.

Now cameras transmit data to the server. Where recognition takes place with the help of special software. The system needs constant access to high-speed internet. Transferring data to the server slows down the process. Network problems stop him altogether.

Generative adversarial models of neural networks come to the fore. Such as GAN is a generative adversarial neural network that consists of a generator and a discriminator. Yang Lecun, Facebook’s director of research for artificial intelligence, called it “the most exciting idea in machine learning in the last ten years.” Generators in the GAN generate input data, and discriminators assess their authenticity. And they classify them into categories using a specific set of features.

The development of generative adversarial networks has made it possible to make a qualitative leap in the recognition. And it’s in generation of human faces. The same GANs create the most realistic images that are indistinguishable from real photos or paintings. True, with the images of animals, things are still much worse.

In addition to static images, neuroavatars are becoming more common. It’s moving images based on 1-32 photos, time-lamps based on landscape photos and modeling 3D scenes based on panoramic photos. The next step is to animate photos using special algorithms.

Suppliers of goods to large retail chains began to supply merchandisers with tablets with special software for photo recognition. Instead of manually checking the availability of goods, their placement and the relevance of the price tags. The sales representative simply takes a photo of the shelf. The system compares it with the planogram and gives recommendations. What product is missing. What is out of place. Where the price tags are mixed up or the current promotion is not indicated. Analyzing the shelves of competitors, the system monitors the share of the shelf in dynamics.

In addition to access control systems, recognition technologies are used to ensure the safety of workers. For example, video analytics systems monitor the wearing of personal protective equipment in hazardous industries: if a person is not wearing a helmet, mask, gloves, or a bright vest, he receives a notification. The signal is sent to his management as well.

At central control consoles it is important to maintain a high level of concentration and not be distracted. And face recognition systems monitor the state of specialists. If a person loses attention or falls asleep, uses the phone, or leaves his post, he and the entire team receive a warning.