Implementation of the identification and recognition system cognitive behavior of the observed

Abstract

This article describes and analyzes the development of a system for identifying and recognizing the cognitive behavior of students to determine interest in facial expressions. The purpose of the study is to find suitable technologies for the implementation of this system. The definition of emotions will allow organizing control over the quality of the educational process, conducting statistics on the cognitive behavior of students during classes and showing the level of interest of students in the material presented. The identification system will automatically determine and register the time of arrival and departure of students in real time. Based on the joint application of the Viola-Jones method and the nearest neighbors method using histograms of centrally symmetric local binary images, a system for face recognition in a real-time video sequence has been developed. The structure of the project is described and software is developed in the Python programming language using the Keras open source library. The developed system consists of two subsystems: an identification system and a cognitive behavior recognition system. The scientific novelty lies in an integrated approach to the development and research of algorithms for real-time face recognition and identification for solving applied problems.