Smartfit: Smartphone application for garment fit detection

Kamrul H. Foysal, Hyo Jung Chang, Francine Bruess, Jo Woon Chong

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The apparel e-commerce industry is growing day by day. In recent times, consumers are particularly interested in an easy and time-saving way of online apparel shopping. In addition, the COVID-19 pandemic has generated more need for an effective and convenient online shopping solution for consumers. However, online shopping, particularly online apparel shopping, has several challenges for consumers. These issues include sizing, fit, return, and cost concerns. Especially, the fit issue is one of the cardinal factors causing hesitance and drawback in online apparel purchases. The conventional method of clothing fit detection based on body shapes relies upon manual body measurements. Since no convenient and easy-to-use method has been proposed for body shape detection, we propose an interactive smartphone application, “SmartFit”, that will provide the optimal fitting clothing recommendation to the consumer by detecting their body shape. This optimal recommendation is provided by using image processing and machine learning that are solely dependent on smartphone images. Our preliminary assessment of the developed model shows an accuracy of 87.50% for body shape detection, producing a promising solution to the fit detection problem persisting in the digital apparel market.

Original languageEnglish
Article number97
Pages (from-to)1-15
Number of pages15
JournalElectronics (Switzerland)
Volume10
Issue number1
DOIs
StatePublished - Jan 2021

Keywords

  • Body shape detection
  • Image processing
  • Machine learning
  • Online shopping
  • Smartphone

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