Journal of Korea Multimedia Society (한국멀티미디어학회논문지)

Korea Multimedia Society (한국멀티미디어학회)
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A Study On User Skin Color-Based Foundation Color Recommendation Method Using Deep Learning

딥러닝을 이용한 사용자 피부색 기반 파운데이션 색상 추천 기법 연구

  • Jeong, Minuk (School of Artificial Intelligence, Daegu University) ;
  • Kim, Hyeonji (School of Artificial Intelligence, Daegu University) ;
  • Gwak, Chaewon (School of Computer Information Engineering, Daegu University) ;
  • Oh, Yoosoo (School of Artificial Intelligence, Daegu University)
  • Received : 2022.04.13
  • Accepted : 2022.08.26
  • Published : 2022.09.30
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Abstract

In this paper, we propose an automatic cosmetic foundation recommendation system that suggests a good foundation product based on the user's skin color. The proposed system receives and preprocesses user images and detects skin color with OpenCV and machine learning algorithms. The system then compares the performance of the training model using XGBoost, Gradient Boost, Random Forest, and Adaptive Boost (AdaBoost), based on 550 datasets collected as essential bestsellers in the United States. Based on the comparison results, this paper implements a recommendation system using the highest performing machine learning model. As a result of the experiment, our system can effectively recommend a suitable skin color foundation. Thus, our system model is 98% accurate. Furthermore, our system can reduce the selection trials of foundations against the user's skin color. It can also save time in selecting foundations.

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References

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