STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Artificial Intelligence Research & Advances Review Article

CHROMAWEAR: An AI Assisted Personalized Fashion Design Recommender System for Diverse Skin Tones to Enhance Fashion Choices

  1. Humaira Naaz Department of Computer Engineering, Jamia Millia Islamia
  2. Shabnam Bano Department of Computer Engineering, Jamia Millia Islamia
  3. Guddu Kumar Department of Computer Engineering, Jamia Millia Islamia
  4. Mohammad Faizan Department of Computer Engineering, Jamia Millia Islamia
  5. Sunil Department of Computer Engineering, Jamia Millia Islamia

Abstract

In the age of fashion, we receive the same question every day: What should I wear today to look nice? The fashion industry is always changing, welcoming inclusivity and diversity. Still, despite the advancements, there are difficulties meeting people's varied needs, especially with regard to skin tone. This research work presents a personalized fashion design recommender system with artificial intelligence support to improve the fashion choices of people with different skin tones. Unlike traditional techniques of physically trying on garments, the skin tonner system uses digital representations to revolutionize the experience of putting on clothing. The system makes customized fashion recommendations by analyzing skin tone and taking into account color palettes, fabric textures, and clothing styles that fit well with the individual's complexion. Through augmented reality and machine learning, the skin tonner system analyses skin tone and body shape to generate abstract digital overlays of clothing for users to interact with in real-time. With the use of numerous algorithms and models, such as the Decision Tree algorithm for recommendation and the K-Means Clustering algorithm for skin tone shade detection, the proposed system seeks to assist the user in selecting what color clothing will suit the individual best on appropriate occasions. We go over the design, implementation process, and assessment criteria of the suggested system, highlighting its potential to transform the fashion business by advancing inclusivity and giving people the power to make educated fashion choices.

Keywords

References (16)

  1. Prof. Narode P. P., Bagul Priyanka S., Pardeshi Vaishali K., Paymode Vaishnavi V., Madhawai Amruta P. Improving Foundation Shade Recommendations using Skin Tone Recognition. International Journal of Advanced Research in Science, Communication and Technology. 2023:668-676. doi:10.48175/ijarsct-14290
  2. Ziccardi G. Wearable Technologies and Smart Clothes in the Fashion Business: Some Issues Concerning Cybersecurity and Data Protection. Laws. 2020;9(2):12. doi:10.3390/laws9020012
  3. Kolkur, Kalbande D, Jatakia J. Human skin detection using rgb, hsv and ycbcr color models. Proceedings of the International Conference on Communication and Signal Processing 2016 (ICCASP 2016). 2016 Feb; 324–332.
  4. Garude D, Khopkar A, Dhake M, Laghane S, Maktum T. Skin-Tone and Occasion Oriented Outfit Recommendation System. SSRN Electronic Journal. 2019. doi:10.2139/ssrn.3368058
  5. Al-Tairi ZH, Rahmat RW, Saripan MI, Sulaiman PS. Skin Segmentation Using YUV and RGB Color Spaces. Journal of Information Processing Systems. 2014;10(2):283-299. doi:10.3745/jips.02.0002
  6. Patil Shankar, Bhanage Simran, Shali Zitin. Automatic Suggestion of Outfits using Image Processing. Int Res J Eng Technol. 2019; 6(4): 4129–4135.
  7. Atharv Pandit, Dwarkadas J.Sanghvi College Of Engineering. A Review on Clothes Matching and Recommendation Systems based on user Attributes. International Journal of Engineering Research and. 2020;V9(08). doi:10.17577/ijertv9is080371
  8. Yuan M, Khan IR, Farbiz F, Yao S, Niswar A, Foo MH. A Mixed Reality Virtual Clothes Try-On System. IEEE Transactions on Multimedia. 2013;15(8):1958-1968. doi:10.1109/tmm.2013.2280560
  9. Siddhesh T, Chetan P, Yaman T, Sumeet KS, Monika D. Suggestion Based Outfit Selection Using Skin Tone Detection in Augmented Reality. Int J Res Appl Sci Eng Technol (IJRASET). 2016; 4(V): 870–872. ISSN: 2321-9653.
  10. Bhure BP, Bansod PT, Amgaokar MS, Lodiwale SP, Orkey AP, Mohod A. A Review on Outfit Fashion Recommendation System. International Journal of Scientific Research in Computer Science, Engineering and Information Technology. 2021:220-222. doi:10.32628/cseit217368
  11. Ying Huang, Tao Huang. Outfit Recommendation System Based on Deep Learning. 2nd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA), Advances in Computer Science Research. 2017; 164–168.
  12. Liu Y, Nie J, Xu L, Chen Y, Xu B. Clothing Recommendation System Based on Advanced User-Based Collaborative Filtering Algorithm. Lecture Notes in Electrical Engineering. 2017:436-443. doi:10.1007/978-981-10-7521-6_53
  13. Journal I. Study of the role that AI can play in the Sustainable Fashion Business. INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT. 2024;08(02):1-10. doi:10.55041/ijsrem28523
  14. Shirkhani S, Mokayed H, Saini R, Chai HY. Study of AI-Driven Fashion Recommender Systems. SN Computer Science. 2023;4(5). doi:10.1007/s42979-023-01932-9
  15. Saturday NR, Igulu KT, Singh TP, Onuodu FE. The Role of Machine Learning/AI in Recommender Systems. Recommender Systems. 2023:69-80. doi:10.1201/9781003319122-5
  16. Wang L. Commerce Product Recommendation Algorithm Based on Collaborative Filtering. Advances in Transdisciplinary Engineering. 2024. doi:10.3233/atde231237
Support