Method of synthetic data generation and architecture of face recognition system for interaction with robots in cyberphysical space

Abstract

In this paper we discuss the problem of user identification in cyberphysical space based on images of user’s face. We have analysed existing methods and approaches of facial recognition. Taking into account this analysis, we propose a new method for generating synthetic samples, which allows you to create datasets for neural network training. Also, we designed architecture of the system itself which provides retraining of the model and selecting the optimal configuration of the neural network. The paper considers scenarios of user interaction with mobile robotic systems within the cyberphysical environment based on the developed face recognition system.