Face Recognition based on Convolutional Neural Network

DOI

10.2991/978-94-6463-300-9_102How to use a DOI?

Keywords

Face recognition; face detection; convolutional Neural Network

Abstract

Facial recognition has always been a focal point of computer vision research, and its goal is to build a model to distinguish between different individual identities. Most of the early face recognition algorithms relied on manual features, such as texture, shape, edge, local binary pattern, etc. However, limited by the lack of feature expression ability, the effectiveness of these methods can't fulfill the genuine application requirements. Thanks to Convolutional neural networks have developed quickly, face identification technology using deep learning, there gradually matured and it has been used in many fields including security monitoring, face payment, and smart home. In this article, a facial recognition algorithm is offered based on FaceNet, which mainly includes data preprocessing, facial detection, face alignment, feature extraction and classifier training modules. I detail the implementation details of each module and conduct large-scale experiments on public data sets. Extensive experience confirms the effectiveness of the proposed methodology. Finally, I also summarize the current problems in the area of face identification research and discuss its future development directions.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Jiahao Zhao
PY  - 2023
DA  - 2023/11/27
TI  - Face Recognition based on Convolutional Neural Network
BT  - Proceedings of the 2023 International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI 2023)
PB  - Atlantis Press
SP  - 1013
EP  - 1023
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-300-9_102
DO  - 10.2991/978-94-6463-300-9_102
ID  - Zhao2023
ER  -