Neural Network Method for Determining The Direction of a Person's Gaze based on a Web Camera Image Analysis

Abstract

Determining the direction of a person's gaze improves the accuracy of the voice control systems, which are relevant in the actively developing voice assistant creation field. This paper proposes a neural network method for determining the gaze direction based on the web camera image analysis. In the course of the paper, a corpus of data was collected and marked up with preprocessed data from the web camera and the point of view direction on the monitor screen. A neural network model was built based on fully connected and convolutional layers. The created neural network model for determining the gaze direction demonstrated an improvement of 13% in pixel error on the monitor screen compared to the existing open-source solutions. The created neural network model was implemented in the voice control system of a mobile robot, which facilitated minimization of the ambiguity in the analysis of movement commands towards objects.