An AI-Assisted Skincare Routine Recommendation System in XR
Gowravi Malalur Rajegowda Yannis Spyridis Barbara Villarini Vasileios Argyriou
In recent years, there has been an increasing interest in the use of
artificial intelligence (AI) and extended reality (XR) in the beauty industry.
In this paper, we present an AI-assisted skin care recommendation system
integrated into an XR platform. The system uses a convolutional neural network
(CNN) to analyse an individual's skin type and recommend personalised skin care
products in an immersive and interactive manner. Our methodology involves
collecting data from individuals through a questionnaire and conducting skin
analysis using a provided facial image in an immersive environment. This data
is then used to train the CNN model, which recognises the skin type and
existing issues and allows the recommendation engine to suggest personalised
skin care products. We evaluate our system in terms of the accuracy of the CNN
model, which achieves an average score of 93% in correctly classifying existing
skin issues. Being integrated into an XR system, this approach has the
potential to significantly enhance the beauty industry by providing immersive
and engaging experiences to users, leading to more efficient and consistent
skincare routines.