Journal of Cognitive Human-Computer Interaction

Journal DOI

https://doi.org/10.54216/JCHCI

Submit Your Paper

2771-1463ISSN (Online) 2771-1471ISSN (Print)

Volume 9 , Issue 2 , PP: 01-10, 2025 | Cite this article as | XML | Html | PDF | Full Length Article

PhyGital Fit: An AI-Driven Virtual Footwear Solution Integrating Generative AI, AR and Foot Morphology Analysis for Personalized Fit

Abhimanyu Sangale 1 * , Nikita Bhawar 2 , Rutuja Gholap 3 , Bhoomi Raut 4 , Kanchan Suryavanshi 5

  • 1 Department of Computer Science Engineering, Sanjivani College of Engineering, Kopargoan, India - (abhimanyusangale@gmail.com)
  • 2 Department of Computer Science Engineering, Sanjivani College of Engineering, Kopargoan, India - (bhawarnikita01@gmail.com)
  • 3 Department of Computer Science Engineering, Sanjivani College of Engineering, Kopargoan, India - (gholaprutuja9@gmail.com)
  • 4 Department of Computer Science Engineering, Sanjivani College of Engineering, Kopargoan, India - (bhoomi.raut07@gmail.com)
  • 5 Department of Computer Science Engineering, Sanjivani College of Engineering, Kopargoan, India - (kanchansuryavanshi@gmail.com)
  • Doi: https://doi.org/10.54216/JCHCI.090201

    Received: January 17, 2025 Revised: March 03, 2025 Accepted: April 14, 2025
    Abstract

    Rapid development has been seen in Artificial Intel license (AI), which has transformed the retail industry, including online shopping. Selecting the right size of shoes that varies with brands and design is one of the biggest challenges in the E-Commerce footwear industry. This research focuses on AI Powered virtual shoe fitting system using Lens Studio Software. In this, customers are able to try shoes virtually through augmented reality and customized 3D foot models. This innovation solves size issues and benefits online footwear retailers, resulting in greater customer satisfaction. The role of Lens Studio software includes the creation of customized shoes, 3D shoes models, lenses, and size accuracy with the foot tracking mechanism.

    Keywords :

    Virtual shoe , Augmented Reality , 3D shoe model , Lens Studio Software , Artificial Intelligence , E-Commerce

    References

    [1]       L. Cao, C. L. P. Koh, and S. K. Wong, "Consumers’ Challenges in Online Shoe Purchasing and Attitude Towards 3D Virtual Shoe Fitting Technology: A Qualitative Study of Women in China," The Design School, Taylor’s University, Malaysia, and Saito University College, Malaysia, 2024.

    [2]       C.-H. Chu, Y.-A. Chen, Y.-Y. Huang, and Y.-J. Lee, "A Comparative Study of Virtual Footwear Try-On Applications in Virtual and Augmented Reality," J. Comput. Inf. Sci. Eng., vol. 22, no. 041003, 2022.

    [3]       C. Chen, J. Ni, and P. Zhang, "Virtual Try-On Systems in Fashion Consumption: A Systematic Review," Appl. Sci., vol. 14, no. 11839, 2024.

    [4]       A. Nestler, N. Karessli, K. Hajjar, and R. Weffer, "SizeFlags: Reducing Size and Fit Related Returns in Fashion E-Commerce," in Proc. 27th ACM SIGKDD Conf. on Knowledge Discovery and Data Mining (KDD ’21), Virtual Event, 2021.

    [5]       Sumithra M., Chezhian, Vettri, Kumar, Raj, Kumar, Nithish, "Automated Attendance System using Real Time Face Recognition and MySQL Database," J. Cognitive Human-Computer Interaction, vol. 2, no. 1, pp. 15-18, 2022. DOI: https://doi.org/10.54216/JCHCI.020102.

    [6]       A. Nestler, N. Karessli, K. Hajjar, R. Weffer, and R. Shirvany, "SizeFlags: Reducing Size and Fit Related Returns in Fashion E-Commerce," arXiv preprint arXiv:2106.03532, 2021.

    [7]       H.-L. Rhee and K.-H. Lee, "Enhancing the Sneakers Shopping Experience through Virtual Fitting using Augmented Reality," Sustainability, vol. 13, no. 6336, 2021.

    [8]       S. Huang, Z. Wang, and Y. Jiang, "Guess Your Size: A Hybrid Model for Footwear Size Recommendation," Adv. Eng. Inform, vol. 36, pp. 64–75, 2018.

    [9]       C. Kaewrat, P. Boonbrahm, and B. Sahoh, "The Design and Development of a Foot-Detection Approach Based on Seven-Foot Dimensions: A Case Study of a Virtual Try-On Shoe System using Augmented Reality Techniques," Informatics, vol. 10, no. 48, 2023.

    [10]    M. Jäger, J. Eberhardt, and D. W. Cunningham, "3D Reconstruction of Partial Foot Scans using Different State-of-the-Art Neural Network Approaches," Footwear Science, vol. 16, pp. 105–114, 2024.

    [11]    Y. Eshel, O. Levi, H. Roitman, and A. Nus, "PreSizE: Predicting Size in E-Commerce using Transformers," in Proc. 44th Int. ACM SIGIR Conf. on Research and Development in Information Retrieval (SIGIR ’21), 2021, pp. 255–264.

    [12]    P. K. Saxena and M. Saini, "Sculpting the Perfect Shoe: A Deep Dive into AI-Driven Footwear Design and Production," Int. J. Multidiscip. Res. (IJFMR), vol. 5, 2023.

    [13]    Sumithra, M., Buvaneswar, B., Judith, J., Mary, D., and R. Punitha, "Innovation for Better Education System using Artificial Intelligence," J. Cognitive Human-Computer Interaction, vol. 2, no. 1, pp. 19-28, 2022. DOI: https://doi.org/10.54216/JCHCI.020103.

    [14]    J. Ren, A. Wang, H. Li, X. Yue, and L. Meng, "A Transformer-Based Neural Network for Gait Prediction in Lower Limb Exoskeleton Robots using Plantar Force," Sensors, vol. 23, no. 6547, 2023.

    [15]    H. Wang, F. Liu, and R. Fan, "A Research on Foot Size Measurement Algorithm Based on Image," J. Phys. Conf. Ser., vol. 1903, no. 012004, 2021.

    [16]    A. Smith and B. Johnson, "Innovative Approaches to Footwear Size Prediction using Machine Learning," Int. J. Fashion Tech., vol. 3, no. 2, pp. 45-52, 2023.

    [17]    C. Li, A. Narayanan, and A. Ghobakhlou, "Overlapping Shoeprint Detection by Edge Detection and Deep Learning," J. Imaging, vol. 10, no. 186, 2024.

    [18]    R. M. K. B. Alavi and S. S. V. R. Srivastava, "A Novel Method for Shoe Sizing using 3D Scanning and Machine Learning," J. Fashion Technol. Textile Eng., vol. 8, no. 1, pp. 25-34, 2023.

    [19]    R. B. Rafiq, K. M. Hoque, M. A. Kabir, S. Ahmed, and C. Laird, "OptiFit: Computer-Vision-Based Smartphone Application to Measure the Foot from Images and 3D Scans," Sensors, vol. 22, no. 9554, 2022.

     

     

    Cite This Article As :
    Sangale, Abhimanyu. , Bhawar, Nikita. , Gholap, Rutuja. , Raut, Bhoomi. , Suryavanshi, Kanchan. PhyGital Fit: An AI-Driven Virtual Footwear Solution Integrating Generative AI, AR and Foot Morphology Analysis for Personalized Fit. Journal of Cognitive Human-Computer Interaction, vol. , no. , 2025, pp. 01-10. DOI: https://doi.org/10.54216/JCHCI.090201
    Sangale, A. Bhawar, N. Gholap, R. Raut, B. Suryavanshi, K. (2025). PhyGital Fit: An AI-Driven Virtual Footwear Solution Integrating Generative AI, AR and Foot Morphology Analysis for Personalized Fit. Journal of Cognitive Human-Computer Interaction, (), 01-10. DOI: https://doi.org/10.54216/JCHCI.090201
    Sangale, Abhimanyu. Bhawar, Nikita. Gholap, Rutuja. Raut, Bhoomi. Suryavanshi, Kanchan. PhyGital Fit: An AI-Driven Virtual Footwear Solution Integrating Generative AI, AR and Foot Morphology Analysis for Personalized Fit. Journal of Cognitive Human-Computer Interaction , no. (2025): 01-10. DOI: https://doi.org/10.54216/JCHCI.090201
    Sangale, A. , Bhawar, N. , Gholap, R. , Raut, B. , Suryavanshi, K. (2025) . PhyGital Fit: An AI-Driven Virtual Footwear Solution Integrating Generative AI, AR and Foot Morphology Analysis for Personalized Fit. Journal of Cognitive Human-Computer Interaction , () , 01-10 . DOI: https://doi.org/10.54216/JCHCI.090201
    Sangale A. , Bhawar N. , Gholap R. , Raut B. , Suryavanshi K. [2025]. PhyGital Fit: An AI-Driven Virtual Footwear Solution Integrating Generative AI, AR and Foot Morphology Analysis for Personalized Fit. Journal of Cognitive Human-Computer Interaction. (): 01-10. DOI: https://doi.org/10.54216/JCHCI.090201
    Sangale, A. Bhawar, N. Gholap, R. Raut, B. Suryavanshi, K. "PhyGital Fit: An AI-Driven Virtual Footwear Solution Integrating Generative AI, AR and Foot Morphology Analysis for Personalized Fit," Journal of Cognitive Human-Computer Interaction, vol. , no. , pp. 01-10, 2025. DOI: https://doi.org/10.54216/JCHCI.090201