Digital makeup

• Main Author: Chua, Zi Jian
• Other Authors: He Ying
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2024
• Subjects: Engineering; Computer science and engineering
• Online Access: https://hdl.handle.net/10356/175268
• Institution: Nanyang Technological University

In today’s progressively digitized world, social media has become the most common platform for people to share their lives and foster connections with others. It is not difficult to find people on social media posting their portrait and self-portrait photographs, and this leads to the increasing demand for photo-editing apps which help them to beautify their photos. However, the majority of the tools are designed for only editing raster images and it is well known that vector graphics provide several practical benefits over raster graphics, including sparse representation, compact storage, geometric editability, information reuse and resolution-independence. Hence, this project presents the use of state-of-the-art machine learning algorithm to develop a digital makeup transfer algorithm which helps users to apply makeup to their portrait images digitally. This project aims to develop a makeup transfer algorithm that edits vector graphics such that image quality is maintained.