The aim of this research is to develop and test the garment size recommendation app, ShapeMate, embedded within a fashion e-commerce site. Not finding the correct garment size causes the high return rate of 30%-40% (According to interviews commissioned by the research project with leading fashion e-commerce and retailers in the UK), in fashion e-commerce. The app captures a single image with minimal user input, to estimate and classify the 3D body shape, in order to generate body measurements and using this information, to match with garment data for size recommendation. An extensive user-experience study was conducted. The developed app was empirically tested through semi-structured focus group interview and questionnaires, to validate results and obtain further insight. This research offers a major innovation for low-cost size recommendation generated from a single image for fashion e-commerce. It enhances the online apparel shopping experience, by matching body measurements with a personalised recommendation for garments.
|Number of pages||8|
|Journal||International Journal of Industrial Engineering and Management|
|Publication status||Published - 2014|
PENG, F., & Al-Sayegh, M. (2014). Personalised virtual fitting for fashion. International Journal of Industrial Engineering and Management, 5(4), 233-240. http://ualresearchonline.arts.ac.uk/9842/1/ijiem_vol5_no4_7.pdf