Research on Face Recognition Technology Based on Real-World Application Scenarios

Yifan Lan

2024

Abstract

Face recognition technology is widely used in various fields has received extensive attention from researchers. This study classifies and summarizes different face recognition methods based on real life. In more detail, this paper is categorized into: masked face recognition and non-masked face recognition according to their application significance. First, each type of face recognition method is summarized and retrospectively compared based on the time series of development. Second, different face recognition methods are implemented based on the same de-emphasized dataset, and the recognition accuracy and execution time of each method are derived. The advantages and disadvantages of different methods are analysed and compared with the basic criteria of these two data metrics. And the experimental data results are visualized for more detailed analysis. The experimental results show that face recognition performance can be improved by introducing deep learning techniques. Therefore, the future direction of face recognition research should be to explore how to integrate different types of face recognition methods to achieve maximum efficiency. This study summarizes the face recognition methods from practical application scenarios, which has certain reference value for enterprises and related technicians.

Paper Citation

in Harvard Style

Lan Y. (2024). Research on Face Recognition Technology Based on Real-World Application Scenarios. In Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI; ISBN 978-989-758-713-9, SciTePress, pages 368-374. DOI: 10.5220/0012938300004508

in Bibtex Style

@conference{emiti24,
author={Yifan Lan},
title={Research on Face Recognition Technology Based on Real-World Application Scenarios},
booktitle={Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI},
year={2024},
pages={368-374},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012938300004508},
isbn={978-989-758-713-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI
TI - Research on Face Recognition Technology Based on Real-World Application Scenarios
SN - 978-989-758-713-9
AU - Lan Y.
PY - 2024
SP - 368
EP - 374
DO - 10.5220/0012938300004508
PB - SciTePress