Abstract
This research focuses on applying AI to evaluate students' performance in makeup learning, aiming to provide them with a self-learning reference tool and professional grading assistance. Use AI technology to verify whether facial makeup can enhance facial appeal. This research has two main goals: to achieve the effectiveness of students' makeup learning through AI technology, thus providing beneficial tools for students learning the art of makeup, to evaluate students' makeup skills in major exams in a fast and fair manner, trying to reduce the biases in judgment standards among different evaluators and ensure the consistency of assessment results. The essence of the study aims to establish a teaching assistant model. Using AI technology to verify whether facial makeup can enhance facial appeal. Where AI rated their facial makeup and bare faces after attending courses, providing scores for before and after their makeups. Comparing the bare and made-up faces of 100 models, the study used specific big data algorithms to distinguish between made-up and bare faces. The results proves that AI can effectively evaluate the results of facial makeup. In addition, the study used a CNN model (ResNet18) trained on the SCUTFBP-5500 public dataset, which contains 5500 images of faces. All the images in the dataset were rated in the scale of five by 60 volunteers and is a widely used benchmark for facial beauty evaluation. We aim to eventually develop a new assisting model for makeup education [1].
Author Information
Fu-Shan Lin, National Tsing-Hua University, Taiwan
Hsiu-Hui Hsu, Lee-Ming Institute of Technology, Taiwan
Yu-Ling Ko, National Tsing Hua University, Taiwan
Wei-Jen Cho, Lee-Ming Institute of Technology, Taiwan
Yeong-Luh Ueng, National Tsing-Hua University, Taiwan
Paper Information
Conference: IICE2024
Stream: Interdisciplinary
This paper is part of the IICE2024 Conference Proceedings (View)
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To cite this article:
Lin F., Hsu H., Ko Y., Cho W., & Ueng Y. (2024) AI, AI, Who Is the Most Beautiful Person in the World? ISSN: 2189-1036 – The IAFOR International Conference on Education – Hawaii 2024 Official Conference Proceedings (pp. 645-653) https://doi.org/10.22492/issn.2189-1036.2024.54
To link to this article: https://doi.org/10.22492/issn.2189-1036.2024.54
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