Issue |
ITM Web Conf.
Volume 70, 2025
2024 2nd International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2024)
|
|
---|---|---|
Article Number | 03007 | |
Number of page(s) | 9 | |
Section | Image Processing and Computer Vision | |
DOI | https://doi.org/10.1051/itmconf/20257003007 | |
Published online | 23 January 2025 |
Comprehensive Analysis of Face Recognition Technologies
Ulster College, Shaanxi University of Science and Technology, 710021 Xi’an, China
Corresponding author: 202215030216@sust.edu.cn
This article provides a comprehensive review of face recognition research, focusing on advancements made over the past century. It presents a detailed examination of the core concepts, principles, steps, and classifications of face recognition technology. The review highlights the practical applications of face recognition in contemporary contexts and summarizes key datasets and preprocessing methods used in the field. The paper categorizes face recognition methods into three main types and places particular emphasis on hybrid methods. It explores the principles and research processes associated with these methods, offering an in-depth analysis of their results. Among the various techniques reviewed, deep learning methods emerge as the most promising for face recognition due to their superior performance. This review serves as a valuable resource for students and novice researchers by providing a clear overview of current research methodologies and tools. Additionally, it outlines potential research directions and contributes to the advancement of the field of computer vision.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.