An AI-Powered Digital Foundation Recommender System

D. M. Ruiz, A. Watson, Y. Kumar, J. J. Li, P. Morreale

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper addresses the significant challenge of selecting suitable foundation shades, particularly for darker skin tones, which have been inadequately represented and catered to in the beauty industry. It introduces an innovative system designed to offer individualized makeup recommendations, significantly diminishing the time and effort traditionally demanded of consumers when searching for appropriate products. Utilizing machine learning methodologies and computer vision techniques, the system analyzes image data to precisely identify a range of skin tones, enabling it to propose compatible foundation shades automatically. Unlike sophisticated Large Language Models, such as ChatGPT, Gemini, Microsoft Copilot, or Claude, which are not equipped to undertake such visually driven tasks due to ethical guidelines that prohibit them from processing personal images without explicit consent and the absence of face image processing capabilities, this technological development represents a step forward in fostering inclusivity, illustrating the transformative potential of AI in accommodating the unique beauty preferences of all individuals.

Original languageEnglish
Title of host publication2024 International Symposium on Networks, Computers and Communications, ISNCC 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350364910
DOIs
StatePublished - 2024
Event2024 International Symposium on Networks, Computers and Communications, ISNCC 2024 - Washington, United States
Duration: 22 Oct 202425 Oct 2024

Publication series

Name2024 International Symposium on Networks, Computers and Communications, ISNCC 2024

Conference

Conference2024 International Symposium on Networks, Computers and Communications, ISNCC 2024
Country/TerritoryUnited States
CityWashington
Period22/10/2425/10/24

Keywords

  • AI-based shade matching
  • computer vision for foundation matching
  • inclusivity in cosmetics
  • personalized foundation shade recommender
  • skin tone classification

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