Humaira Naaz,
Shabnam Bano,
Guddu Kumar,
Mohammad Faizan,
Sunil,
- Student Computer Engineering, Department of University Polytechnic, Faculty of Engineering & Tech-nology, Jamia Millia Islamia New Delhi India
- Student Computer Engineering, Department of University Polytechnic, Faculty of Engineering & Tech-nology, Jamia Millia Islamia New Delhi India
- Student Computer Engineering, Department of University Polytechnic, Faculty of Engineering & Tech-nology, Jamia Millia Islamia New Delhi India
- Student Computer Engineering, Department of University Polytechnic, Faculty of Engineering & Tech-nology, Jamia Millia Islamia New Delhi India
- Associate Professor Computer Engineering, Department of University Polytechnic, Faculty of Engineering & Tech-nology, Jamia Millia Islamia New Delhi India
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 recommen-dations 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 gen-erate 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 recom-mendation and the K-Means Clustering algorithm for skin tone shade detection, the pro-posed system seeks to assist the user in selecting what color clothing will suit the indi-vidual 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: Artificial Intelligence (AI), Fashion Design, Recommender System, Skin Tone, Diversi-ty, Inclusivity.
[This article belongs to Journal of Artificial Intelligence Research & Advances(joaira)]
References
- P., Prof & S., Bagul & K., Pardeshi & V., Paymode & P, Madhawai.: Improving Foundation Shade Recommendations using Skin Tone Recognition. International Journal of Advanced Research in Science, Communication and Technology. 668-676. 10.48175/IJARSCT-14290 (2023).
- Ziccardi, Giovanni.: Wearable Technologies and Smart Clothes in the Fashion Business: Some Issues Concerning Cybersecurity and Data Protection. Laws. 9. 12. 10.3390/laws9020012 (2020).
- P. S. C. B. S. Kolkur, D. Kalbande, and J. Jatakia.: Human skin detection using rgb, hsv and ycbcr color models. February (2016).
- Garude, Digant & Khopkar, Anushree & Dhake, Monali & Laghane, Shivani & Maktum, Tabassum.: Skin-Tone and Occasion Oriented Outfit Recommendation System. SSRN Electronic Journal. 10.2139/ssrn.3368058 (2019).
- Kolkur, S. & Kalbande, Dhananjay & Shimpi, P. & Bapat, C. & Jatakia, Janvi.: Human Skin Detection Using RGB, HSV and YCbCr Color Models. 10.2991/iccasp-16.2017.51 (2017).
- Patil, Shankar & Bhanage, Simran & Shali, Zitin.: Automatic Suggestion of Outfits using Image Processing. 6 (2019).
- Atharv, P.: A Review on Clothes Matching and Recommendation Systems based on user Attributes. International Journal of Engineering Research and. V9. 10.17577/IJERTV9IS080371 (2020).
- Yuan, Miaolong & Khan, Ishtiaq & Farbiz, Farzam & Yao, S.s.: A Mixed Reality Virtual Clothes Try-on System. 10.1109/TMM.2013.2280560 (2013).
- Siddhesh T., Chetan P., Yaman T., Sumeet K. S.,Prof.Monika D.: Suggestion Based Outfit Selection Using Skin Tone Detection in Augmented Reality. International Journal for Research in Applied Science & Engineering Technology (IJRASET), Volume 4 Issue V, ISSN: 2321-9653 (2016).
- Bhure, Bhagyshree & Bansod, Pratiksha & Amgaokar, Monali & Lodiwale, Savita & Orkey, Anjali & Mohod, Ashish.: A Review on Outfit Fashion Recommendation System. International Journal of Scientific Research in Computer Science, Engineering and Information Technology. 220-222. 10.32628/CSEIT217368 (2021).
- 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, volume 74 (2017).
- Liu, Yu & Nie, Jingwen & Xu, Lexi & Chen, Yue & Xu, Bingyu.: Clothing Recommendation System Based on Advanced User-Based Collaborative Filtering Algorithm. 10.1007/978-981-10-7521-6_53 (2018).
- Syed M A, Yash S, Pragati V, Siniya V.: Study of the role that AI can play in the Sustainable Fashion Business. International Journal of Scientific Research in Engineering and Management (IJSREM). 10.10.55041/IJSREM28523 (2024).
- Shirkhani, Shaghayegh & Mokayed, Hamam & Saini, Rajkumar & Hum, Yan.: Study of AI-Driven Fashion Recommender Systems. SN Computer Science. 10.1007/s42979-023-01932-9 (2023).
- Saturday, Nne & Igulu, Kingsley & Singh, Thipendra P & Onuodu, F.: The Role of Machine Learning/AI in Recommender Systems. 10.1201/9781003319122-5 (2023).
- Wang, Linyi.: Commerce Product Recommendation Algorithm Based on Collaborative Filtering. Intelligent Computing Technology and Automation. 10.3233/ATDE231237 (2024).
Journal of Artificial Intelligence Research & Advances
| Volume | 11 |
| Issue | 02 |
| Received | March 24, 2024 |
| Accepted | June 11, 2024 |
| Published | July 10, 2024 |