skip to main content

Clothing size recommender on real-time fitting simulation using skeleton tracking and rigging

Department of Informatics Engineering, Universitas Trunojoyo Madura, Indonesia

Received: 11 Nov 2019; Revised: 20 Feb 2020; Accepted: 24 Feb 2020; Available online: 11 Mar 2020; Published: 30 Apr 2020.
Open Access Copyright (c) 2020 Jurnal Teknologi dan Sistem Komputer
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Citation Format:
Abstract
Virtual fitting room (VFR) is a technology that replaces conventional fitting rooms. The VFR is not only available in shops, malls, and any shopping center but also in online stores, which makes VFR technology more and more developed, primarily to support online garment sales. VFR become a trending research interest since Microsoft has developed a Kinect tracking system. In this paper, we proposed the interactive 3D virtual fitting room using Microsoft's Kinect tracking and the rigging technique from 3D Modeling Blender and to implement the VFR. VFR manages the progress of virtual fitting that forms the three-dimensional simulations and visualization of garments on virtual counterparts of the real prospective buyer (user). Users can view the clothing animation on the various poses that are following the user body movements. The system can evaluate the user’s match, guiding them to choose the suitable size of the clothes using Euclidean distance.
Keywords: virtual fitting room; recommendation system; Kinect; clothing size; body movements
Funding: Universitas Trunojoyo Madura

Article Metrics:

  1. N. Y. Albany, “Virtual fitting room market - influential factors determining the trajectory of the market,” Transparency Market Research, SBWIRE, 2017. [online]. Available: http://www.sbwire.com/press-releases/virtual-fitting-room-market/release-779312.htm
  2. C. A. B. Rodriquez, “Virtual fitting room,” Master thesis, Universidad Politecnica De Madrid, Spain, 2016
  3. V. Kulkarni, S. Morde, B. Pawar, S. Mahadik, and R. Dahore, “2D virtual trial room using augmented reality,” International Journal on Future Revolution in Computer Science & Communication Engineering, vol. 4, no. 1, pp. 226-228, 2018
  4. J. P. Bansidhar, B. S. Hiraman, M. K. Tanaji, S. V. More, and B. S. Shirole, “A virtual dressing room using Kinect,” International Journal of Scientific Research in Science and Technology, vol. 3, no. 3, pp. 384-389, 2017
  5. I. Pachoulakis and K. Kapetanakis, “Augmented reality platforms for virtual fitting rooms,” The International Journal of Multimedia & Its Applications (IJMA), vol. 4, no. 4, pp. 35-46, 2012. doi: 10.5121/ijma.2012.4404
  6. C. Cheng, D. S. Liu, C. Tsai, and L. Chen, “A 3D virtual show room for online apparel retail shop,” in 2009 APSIPA Annual Summit and Conference, Sapporo, Japan, Oct. 2009, pp. 193-199
  7. M. Szymczyk, “When to use 2D vs. 3D virtual dressing room technology,” Zugara, 2019. [online]. Available: http://zugara.com/when-to-use-2d-vs-3d-virtual-dressing-room-technology
  8. A. Kusumaningsih, A. Kurniawati, C.V. Angkoso, E.M. Yuniarno, and M. Hariadi, “User experience measurement on virtual dressing room of Madura batik clothes,” in International Conference on Sustainable Information Engineering and Technology, Malang, Indonesia, Nov. 2017, pp. 203-208. doi: 10.1109/SIET.2017.8304135
  9. F. Pereira, C. Silva, and M. Alves, “Virtual fitting room augmented reality techniques for e-commerce,” in International Conference on ENTERprise Information Systems, Vilamoura, Portugal, Oct. 2011, pp. 62-71. doi: 10.1007/978-3-642-24355-4_7
  10. M. Kotan and C. Öz, “Virtual dressing room application with virtual human using Kinect sensor,” Journal of Mechanics Engineering and Automation, vol. 5, pp 322-326, 2015. doi: 10.17265/2159-5275/2015.05.008
  11. K. W. Mok, C. T. Wong, S. K. Choi, and L. M. Zhang, “Design and development of virtual dressing room system based on Kinect,” International Journal Information Technology and Computer Science, vol. 9, pp. 39-46, 2018. doi: 10.5815/ijitcs.2018.09.05
  12. L. Ziquan, “Augmented reality: virtual fitting room using Kinect,” B. Comp. Dissertation, National University of Singapore, Singapore, 2012
  13. A. Shingade and A. Ghotkar, “Animation of 3D human model using markerless motion capture applied to sports,” International Journal of Computer Graphics & Animation (IJCGA), vol. 4, no. 1, pp. 27-39, 2014. doi: 10.5121/ijcga.2014.4103
  14. R. Rizaldi, A. Kurniawati, and C. V. Angkoso, “Implementasi metode Euclidean distance untuk rekomendasi ukuran pakaian pada aplikasi ruang ganti virtual,” Jurnal Teknologi Informasi dan Ilmu Komputer, vol. 5, no. 2, pp. 129-138, 2018. doi: 10.25126/jtiik.201852592

Last update:

  1. Exploring student experiences with a virtual learning environment in an apparel and textiles curriculum during the COVID-19 pandemic

    Chanmi Hwang, Armine Ghalachyan, Serena Song. International Journal of Fashion Design, Technology and Education, 16 (3), 2023. doi: 10.1080/17543266.2022.2158237
  2. A Proposal for Clothing Size Recommendation System Using Chinese Online Shopping Malls: The New Era of Data

    Ying Yuan, Myung-Ja Park, Jun-Ho Huh. Applied Sciences, 11 (23), 2021. doi: 10.3390/app112311215
  3. Virtual Design Method of Customized Clothing Based on Three-Dimensional Image

    Fengxian Hou, Xiaofen Ji, Le Sun. Mobile Information Systems, 2022 , 2022. doi: 10.1155/2022/9607091
  4. [Retracted] Study on 3D Clothing Color Application Based on Deep Learning‐Enabled Macro‐Micro Adversarial Network and Human Body Modeling

    Jingmiao Liu, Yu Ren, Xiaotong Qin, Syed Hassan Ahmed. Computational Intelligence and Neuroscience, 2021 (1), 2021. doi: 10.1155/2021/9918175
  5. Study on 3D Clothing Color Application Based on Deep Learning-Enabled Macro-Micro Adversarial Network and Human Body Modeling

    Jingmiao Liu, Yu Ren, Xiaotong Qin, Syed Hassan Ahmed. Computational Intelligence and Neuroscience, 2021 , 2021. doi: 10.1155/2021/9918175

Last update: 2024-11-03 02:24:58

  1. Study on 3D Clothing Color Application Based on Deep Learning-Enabled Macro-Micro Adversarial Network and Human Body Modeling

    Jingmiao Liu, Yu Ren, Xiaotong Qin, Syed Hassan Ahmed. Computational Intelligence and Neuroscience, 2021 , 2021. doi: 10.1155/2021/9918175