Comparative characteristics of modern methods of recognition of people on the basis of computer processing of their image

Abstract

The problem of automated recognition of faces and gestures is relatively new and has not yet been fully resolved. In recent years, a number of different methods and algorithms have been proposed for processing, localizing and recognizing faces and gestures in static images, such as «own faces» (Principal Component Analysis, PCA), neural networks, evolutionary algorithms, AdaBoost algorithm, support vector method, etc. However, these approaches for recognizing objects have insufficient accuracy, reliability, and speed in a complex real environment characterized by the presence of noise in images and video sequences. Nowadays CCTV systems have become very widespread. There are so many companies that release their equipment for this purpose. These are video capture cards with special software. But there are problems, of course, this is software that is made for a certain range of tasks, in most cases it is very disturbing. For example, in order for the surveillance system at the checkpoint to calculate the number of passing people, it is necessary to pay a considerable amount of money, since it requires special software processing of the video stream in order to realize it in order to programmatically recognize the images and to calculate them. It should be noted that there are a number of factors that complicate the recognition of objects in static images and video sequences. These include: changing lighting conditions during the shooting process, poor quality of video images, the difficulty of separating the object from the background, the presence of many objects in the video frame, etc. This article discusses the task of detecting objects in an image, as well as methods for processing and analyzing data. The recognition methods, which are one of the first practical tasks, are studied, which has become an incentive for the development of the theory of object recognition. The issues of recognition of faces and gestures, which finds application in various fields of human activity, are analyzed. In this paper, face recognition algorithms are considered.