275
Views
1
CrossRef citations to date
0
Altmetric
Research Articles

Garment fit evaluation using neural networks technology

ORCID Icon, , , , , , , & show all
Pages 562-572 | Received 27 Feb 2020, Accepted 29 Jan 2023, Published online: 18 Apr 2023

References

  • Ashdown, S. P., Loker, S., Schoenfelder, K., & Lyman-Clarke, L. (2004). Using 3D scans for fit analysis. Journal of Textile and Apparel, Technology and Management, 4(1), 1–12.
  • Banerjee, S. S., Mohapatra, S., & Saha, G. (2021). Developing a framework of artificial intelligence for fashion forecasting and validating with a case study. International Journal of Enterprise Network Management, 12(2), 165–180. https://doi.org/10.1504/IJENM.2021.10039608
  • Chen, C. M. (2007). Fit evaluation within the made‐to‐measure process. International Journal of Clothing Science and Technology, 19(2), 131–144. https://doi.org/10.1108/09556220710725720
  • Erwin, M. D., Kinchen, L. A., & Peters, K. A. (1979). Clothing for moderns. Macmillan.
  • Foysal, K. H., Chang, H. J., Bruess, F., & Chong, J. W. (2021). SmartFit: Smartphone application for garment fit detection. Electronics, 10(1), 97. https://doi.org/10.3390/electronics10010097
  • Gill, S. (2015). A review of research and innovation in garment sizing, prototyping and fitting. Textile Progress, 47(1), 1–85. https://doi.org/10.1080/00405167.2015.1023512
  • Gu, X., Gao, F., Tan, M., & Peng, P. (2020). Fashion analysis and understanding with artificial intelligence. Information Processing & Management, 57(5), 102276. https://doi.org/10.1016/j.ipm.2020.102276
  • Guo, Z., Wong, W. K., Leung, S., & Li, M. (2011). Applications of artificial intelligence in the apparel industry: A review. Textile Research Journal, 81(18), 1871–1892. https://doi.org/10.1177/0040517511411968
  • Hernández, N., Mattila, H., & Berglin, L. (2018). A systematic model for improving theoretical garment fit. Journal of Fashion Marketing and Management: An International Journal, 22(4), 527–539. https://doi.org/10.1108/JFMM-10-2017-0112
  • Hong, Y., Bruniaux, P., Zeng, X., Liu, K., Chen, Y., & Dong, M. (2017). Virtual reality-based collaborative design method for designing customized garment for disabled people with scoliosis. International Journal of Clothing Science and Technology, 29(2), 226–237. https://doi.org/10.1108/IJCST-07-2016-0077
  • Javaid, M., Haleem, A., Singh, R. P., & Suman, R. (2022). Artificial intelligence applications for industry 4.0: A literature-based study. Journal of Industrial Integration and Management, 07(01), 83–111. https://doi.org/10.1142/S2424862221300040
  • Kasambala, J., Kempen, E., & Pandarum, R. (2016). Determining female consumers’ perceptions of garment fit, personal values and emotions when considering garment sizing. International Journal of Consumer Studies, 40(2), 143–151. https://doi.org/10.1111/ijcs.12236
  • Kim, H. E., Kwon, J. H., & Kim, J.-J. (2021). Neural correlates of garment fit and purchase intention in the consumer decision-making process and the influence of product presentation. Frontiers in Neuroscience, 15, 609004. https://doi.org/10.3389/fnins.2021.609004
  • Lee, E., & Park, H. (2017). 3D Virtual fit simulation technology: Strengths and areas of improvement for increased industry adoption. International Journal of Fashion Design, Technology and Education, 10(1), 59–70. https://doi.org/10.1080/17543266.2016.1194483
  • Li, C., & Cohen, F. (2021). In-home application (App) for 3D virtual garment fitting dressing room. Multimedia Tools and Applications, 80(4), 5203–5224. https://doi.org/10.1007/s11042-020-09989-x
  • Liechty, E., Rasband, J., & Pottberg-Steineckert, D. (2016). Fitting and pattern alteration: a multi-method approach to the art of style selection, fitting, and alteration. Bloomsbury Publishing USA.
  • Lin, Y.-L., & Wang, M.-J J. (2016). The development of a clothing fit evaluation system under virtual environment. Multimedia Tools and Applications, 75(13), 7575–7587. https://doi.org/10.1007/s11042-015-2681-7
  • Liu, K., Wu, H., Zhu, C., Wang, J., Zeng, X., Tao, X., & Bruniaux, P. (2022). An evaluation of garment fit to improve customer body fit of fashion design clothing. The International Journal of Advanced Manufacturing Technology, 120(3-4), 2685–2699. https://doi.org/10.1007/s00170-022-08965-z
  • Liu, K., Zeng, X., Bruniaux, P., Wang, J., Kamalha, E., & Tao, X. (2017). Fit evaluation of virtual garment try-on by learning from digital pressure data. Knowledge-Based Systems, 133, 174–182. https://doi.org/10.1016/j.knosys.2017.07.007
  • Lu, Y., Song, G., & Li, J. (2014). A novel approach for fit analysis of thermal protective clothing using three-dimensional body scanning. Applied Ergonomics, 45(6), 1439–1446. https://doi.org/10.1016/j.apergo.2014.04.007
  • Miell, S., Gill, S., & Vazquez, D. (2018). Enabling the digital fashion consumer through fit and sizing technology. Journal of Global Fashion Marketing, 9(1), 9–23. https://doi.org/10.1080/20932685.2017.1399083
  • Mohammadi, S. O., & Kalhor, A. (2021). Smart fashion: A review of AI applications in virtual try-on & fashion synthesis. Journal of Artificial Intelligence and Capsule Networks, 3(4), 284–304. https://doi.org/10.36548/jaicn.2021.4.002
  • Oosthuizen, K., Botha, E., Robertson, J., & Montecchi, M. (2021). Artificial intelligence in retail: The AI-enabled value chain. Australasian Marketing Journal, 29(3), 264–273. https://doi.org/10.1016/j.ausmj.2020.07.007
  • Papachristou, E., Chrysopoulos, A., & Bilalis, N. (2021). Machine learning for clothing manufacture as a mean to respond quicker and better to the demands of clothing brands: A Greek case study. The International Journal of Advanced Manufacturing Technology, 115(3), 691–702. https://doi.org/10.1007/s00170-020-06157-1
  • Pawlicka, K., & Bal, M. (2022). Sustainable supply chain finances implementation model and artificial intelligence for innovative omnichannel logistics. Management, 26(1), 19–35. https://doi.org/10.2478/manment-2019-0082
  • Petrova, A., & Ashdown, S. P. (2012). Comparison of garment sizing systems. Clothing and Textiles Research Journal, 30(4), 267–284. https://doi.org/10.1177/0887302X12463603
  • Seo, J.-I., & Namwamba, G. W. (2018). Fit issues in ready-to-wear clothing for African-American female college students based on the body shapes. International Journal of Fashion Design, Technology and Education, 11(2), 160–168. https://doi.org/10.1080/17543266.2017.1354085
  • Shin, E., & Damhorst, M. L. (2018). How young consumers think about clothing fit? International Journal of Fashion Design, Technology and Education, 11(3), 352–361. https://doi.org/10.1080/17543266.2018.1448461
  • Song, H. K., & Ashdown, S. P. (2010). An exploratory study of the validity of visual fit assessment from three-dimensional scans. Clothing and Textiles Research Journal, 28(4), 263–278. https://doi.org/10.1177/0887302X10376411
  • Song, H. K., Kim, Y., & Ashdown, S. P. (2021). Expert versus novice assessment of clothing fit; an exploratory study using eye tracking technology. Fashion Practice, 13(2), 227–252. https://doi.org/10.1080/17569370.2020.1781375
  • Sun, Q., & Sun, X. (2021). Research on the technology of mass customization of clothing. International Journal of Modeling and Optimization, 11(3), 86–93. https://doi.org/10.7763/IJMO.2021.V11.783
  • Taya, Y., Shibuya, A., & Nakajima, T. (1995). Evaluation method of clothing fitness with body Part: 1 Evaluation index of clothing fitness. Sen’i Kikai Gakkaishi (Journal of the Textile Machinery Society of Japan), 48(2), T48–T55. https://doi.org/10.4188/transjtmsj.48.2_T48
  • Wang, Y.-X., & Liu, Z.-D. (2020). Virtual clothing display platform based on CLO3D and evaluation of fit. Journal of Fiber Bioengineering and Informatics, 13(1), 37–49. https://doi.org/10.3993/jfbim00338
  • Wong, W.-K., Guo, Z., & Leung, S. (2014). Intelligent multi-objective decision-making model with RFID technology for production planning. International Journal of Production Economics, 147, 647–658. https://doi.org/10.1016/j.ijpe.2013.05.011
  • Workman, J. E., & Lentz, E. S. (2000). Measurement specifications for manufacturers’ prototype bodies. Clothing and Textiles Research Journal, 18(4), 251–259. https://doi.org/10.1177/0887302X0001800404
  • Yang, G., Ji, G., & Tan, K. H. (2022). Impact of artificial intelligence adoption on online returns policies. Annals of Operations Research, 308(1-2), 703–726. https://doi.org/10.1007/s10479-020-03602-y
  • Yu, M., Wang, Y., Wang, Y., & Li, J. (2013). Correlation between clothing air gap space and fabric mechanical properties. Journal of the Textile Institute, 104(1), 67–77. https://doi.org/10.1080/00405000.2012.693274
  • Zeba, G., Dabić, M., Čičak, M., Daim, T., & Yalcin, H. (2021). Technology mining: Artificial intelligence in manufacturing. Technological Forecasting and Social Change, 171, 120971. https://doi.org/10.1016/j.techfore.2021.120971
  • Zhang, C., & Lu, Y. (2021). Study on artificial intelligence: The state of the art and future prospects. Journal of Industrial Information Integration, 23, 100224. https://doi.org/10.1016/j.jii.2021.100224
  • Zhao, X., Fan, K., Shi, X., & Liu, K. (2021). Virtual fit evaluation of pants using the Adaptive Network Fuzzy Inference System. Textile Research Journal, 91(23-24), 2786–2794. https://doi.org/10.1177/00405175211020515

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.