MASKED FACE RECOGNITION: AN EXAMINATION OF FACIAL RECOGNITION PERFORMANCE UNDER OBFUSCATION CONDITIONS

Abstract

The purpose of this thesis is to examine the impact of obfuscation on the performance of facial recognition algorithms. The primary form of obfuscation is facial masking, due to the immediate relevance of widespread adoption during the pandemic era, and the potential impact of this practice on the reliability of facial recognition. The work begins by replicating recent work [1] and comparing the results. The study then examines a new dataset "SpeakingFaces", and generates the obfuscation set by using the open-source "MaskTheFace" script. The set of facial recognition techniques are applied to the obfuscated dataset, and the results evaluated. The work consists of seven chapters. The first chapter describes the motivation for using masked face recognition technology to authenticate users to ensure security and confidentiality. The objectives of this thesis are presented in detail, and the stages and procedures for the development of this system are described. A brief historical overview of the emergence of this subject area is also presented. The second chapter describes the results of previous studies based on a review of the relevant literature. A survey and comparative analysis of recently published works on creating synthetic datasets and systems for recognizing masked faces, which were used as the basis of this thesis, is being carried out. The third chapter presents the architecture of the masked face recognition system, which is a replication of previously conducted other research works. This work contains the basic architecture of the face recognition system, a model based on a trained neural network and an assessment of the accuracy of face recognition both with and without a mask. These segments have a detailed description with specific templates and parameter settings. The fourth chapter describes in detail the creation of a dataset using open-source MTCNN scripts based on mxnet and TheMaskFace, and using these scripts, the processes of creating datasets designed for the masked face recognition system. This section describes the collection methods, data attributes, constraints, and preprocessing required to use the data. We evaluate the system’s accuracy based on the achievements of other researchers. The fifth chapter describes the detailed implementation of the previously selected research work. All the results of the previous chapters are considered, and the known shortcomings of previous works are considered. The sixth chapter presents all the achievements achieved within the masked face recognition system framework. The analysis of the operation of the facial recognition system in masks with an artificially created dataset and comparison with other datasets is carried out. A comprehensive accuracy assessment and performance analysis is reported. The goals and objectives of the thesis are analyzed with comments on potential shortcomings of the work and completed. The seventh chapter presents the final part of the research work. The results obtained during the research work, the time and performance constraints, and the work planned in the future are described.