SING COMPUTER VISION ALGORITHMS TO IDENTIFY MOVING OBJECTS

There are no universal algorithms for solving problems of recognizing moving objects by video surveillance systems. However, for different systems and in the case of different situations, only some specific algorithm is optimal, allowing for object recognition. This article analyzes the stability of intelligent algorithms that affect the quality of speech recognition and considers an integrated approach that integrates object detection, classification of people, and recognition of gender differences. The accumulated experience in the field of pattern recognition has allowed us to achieve high results in the creation of various devices and systems in medicine, in the industrial sector, in information processing systems and video surveillance. However, computer vision technologies and optical recognition of dynamic objects continue to be an extremely difficult part of scientific research due to the variety of video cameras and devices. As well as a wide range of applications, primarily for security purposes in crowded places, disorder detection, etc. This study presents the main tasks for developing a software system using computer vision and deep learning algorithms to identify and classify people in video streams, determine their number and determine their gender.