Technologies of the future in the present: machine and computer vision and facial biometrics
Faster, more precisely, more effective — these requirements are being put forward today for most processes in our life
Computer and machine vision technologies help a person achieve their implementation. What is it? Where are these technologies applied, and how are they related to facial biometrics? Sorting out the RecFaces team.
Contents
- Sorting out the concepts
- How do computers “see”?
- Why is computer vision needed?
- Where is computer vision used?
- Computer vision and biometrics
Sorting out the concepts
At first glance, it seems that both terms mean the same thing. In fact, it is wrong to consider them. Computer vision is a field of computer science closely related to artificial intelligence and robotics. At the head of the scientific field is the development of technology that allows computers to extract information from images and videos of objects in the real world, and then analyze it. Based on the processed data, the computer is able to find and recognize certain objects, classify by given characteristics, and also track movements. In addition, computer vision is also able to analyze graphs, tables and text. Machine vision is a subsection of computer vision, most often used in industry and manufacturing. As a rule, such systems are aimed for the implementation of specific application tasks: to identify a defect in a part, to recalculate the number of units of production that have descended from the assembly line, and so on. The principle of their work is the same: information analysis based on image capture and processing.
How do computers “see”?
The operation of the computer vision program consists of three stages. The first is to receive an image from a touch device in real time. The sensor is usually a photo or video camera. But it can also be “highly specialized” devices, for example, medical imaging devices. Photos, videos, or 3D models are used as the image. The second stage is picture processing. The first technologies used statistical methods. But today the gold standard is deep learning and a neural network algorithm. With their help, the program begins to save data on each processed image, gradually starting to train itself. The analysis becomes even more accurate. The third step is to decrypt the received image when the computer identifies and classifies the desired objects. Depending on the processing purposes, the following functions are used:
- Identification — the system recognizes the desired object from the picture and analyzes its appearance. The most striking example of identification is the person’s identity verification in a photo or video
- Classification — the computer splits objects in the picture into groups according to a certain characteristic. For example, distinguishes humans from animals or counts the number of necessary items
- Tracking — an analysis of the moment and location of the object or person of interest in the video
- Character Recognition — used to convert letters and numbers in a picture into text
Why is computer vision needed?
Being one of the fields of artificial intelligence, computer vision is focused on the automation of those tasks that in previous centuries or decades were carried out by people. And specifically, those that require imitation of a person's vision and its perception of surrounding objects. The computer adopts our ability to see, but is it able to completely replace man? This is a difficult question. Although artificial intelligence is getting closer to the human mind in its level, computers still do not know how to use abstract thinking or fantasy. Still, computer vision has two big advantages over humans. This is the ability to perceive an infinite number of objects. And also increased work capacity. Unlike a person, the computer does not get tired and does not lose concentration. Let's imagine the operator of the video surveillance system. He must sit in one place for hours, peer at the screen and watch if an emergency arises on the territory. No matter how many cameras or how convenient the surveillance monitors are, in a couple of hours a person will simply get tired, stop adequately perceiving what is happening on the monitor, and is more likely to miss something important. This cannot happen to a computer. Therefore, in everything related to interaction with visual information, computer vision really copes with work faster and more accurately.
Where is computer vision used?
- Industry is the area where computer vision is being introduced most actively today. The technology is used to control the quality of products and packaging, identify defects, count the number of released units of goods, monitor the state of the production-line. All this allows you to reduce costs and increase the profitability of production
- Agriculture — the technology is used to analyze images of fields taken from the air. The data obtained allows you to maintain the desired level of irrigation of crops, track the growth of crops and keep records of the collection. And also fight weeds and plant diseases
- Transport — another promising area for the introduction of computer vision. Autopilot is a striking example. Their existence is entirely based on the development of technology, because it is the computer that monitors the state of the road in real time, the presence of other cars or road signs
- Healthcare — computer vision helps in the diagnosis of various diseases, significantly increasing the quality of basic medical examinations: X-ray, MRI or ultrasound. Moreover, technology often manages to identify the problem at an early stage, when it is simply impossible to see it. And in the future, computers will be able to replace classic diagnostic devices. Such examinations will not only be more accurate, but safer for patients due to lower doses of radiation. And of course, computer vision will become the locomotive of the development of robotics surgery
- Retail — the technology is actively adapting to the needs of trade. And not only for protection against shoplifting, but also for trade turnover, accounting for goods, control over product distribution, monitoring shelf life, contactless payment «by face»
Computer vision and biometrics
Biometrics is one of the subsections or directions of computer vision. And this is the segment of technology with which the average person is well acquainted. The main principle of operation here is the same: the cameras transmit a picture to the facial recognition program. The program processes the image, “finds” the person's face in it and determines a unique set of its unchangeable parameters. Based on them, a biometric template is formed, and then it is compared with those templates that are stored in the program database. If there is a match or no match, the installed action script is run. For example, this could be alerting security personnel to the presence of a suspicious person in the building. Or the opening of a “biometric” turnstile. The facial recognition function expands the use of computer vision in almost all areas. Moreover, identification is often the most demanded function of computer vision. In addition, biometrics works with people. This means that it helps to level in various processes the negative effect of the human factor. Let's consider the main tasks of facial biometrics and see what benefits it brings to the already mentioned areas.
Physical security is a key feature of facial recognition. The introduction of facial biometrics in video surveillance systems significantly increases security both in one facility (for example, a plant or a fuel and energy complex station), and throughout the city. City systems of smart video surveillance allow you to track the situation on the streets and at transport infrastructure facilities: in the metro, at stops, and so on. Biometrics helps prevent security incidents, including terrorist attacks, and also increases the effectiveness of their investigations. Modern facial recognition algorithms are also used to ensure the safety of employees at work. So, with the help of the system, you can make sure that all workers use protective equipment and comply with safety precautions.
Information security. Data protection today is often no less important than physical perimeter or employee protection. This is relevant for everyone from industrial enterprises to medical clinics and from public institutions to banks. Integration of facial biometrics products into service computer systems allows you to control access to company information resources and prevent possible data theft or breach.
Financial transactions. Biometric data, due to its uniqueness and inalienability, become a more reliable alternative to passwords or pin codes. Therefore, today biometrics is actively used to identify customers in the banking sector, including during remote service. And the face payment from the technology of the future in recent years has managed to become quite a technology of the present. In different countries, it is successfully used both to pay in public transport and to pay for purchases in cafes or shops.
Personalization of services. The use of facial biometrics in retail makes customer service more personalized. Recognizing the buyer “in person”, the system itself forms special offers for him or offers discounts on categories of goods interesting to him.
Data Analytics. Biometrics is a convenient tool for collecting reliable data. And reliable data is always of great value, because their analysis can be used for almost any purpose. For example, having statistics on passenger traffic during peak hours, we can adjust routes and traffic intensity on the most popular metro or ground transport lines. And knowing exactly how many people went into our store at different periods, it can evaluate the effectiveness of a particular marketing campaign or the attractiveness of different types of window dressing.
Total automation is treated differently. Someone sees in it the only possible vector of technology development. Others fear humanity will lose competition to robots. But whether we want it or not, both our present and our future are inseparable from the automation trend. In 2020, the global machine vision market was estimated at $9.45 billion, and by 2030 this figure could reach $41.11 billion USD. Face recognition is not only one of the key functions of computer vision, but allows you to significantly expand the scope of this technology. Therefore, as the demand for computer vision grows, software solutions based on facial biometrics will continue to improve and popularize.
