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Personalised Virtual Fitting for Fashion

机译:个性化时尚虚拟装

摘要

The paper describes the "Body Shape Recognition for Online Fashion" research project and the development and testing of 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.
机译:本文介绍了“在线时尚的身体形状识别”研究项目,以及嵌入在时尚电子商务网站中的服装尺寸推荐应用ShapeMate的开发和测试。未找到正确的服装尺寸会导致时尚电子商务中30%-40%的高回报率(根据研究项目委托英国领先的时尚电子商务和零售商进行的采访)。该应用程序只需最少的用户输入即可捕获单个图像,以估计和分类3D身体形状,以便生成身体测量结果并使用此信息与服装数据匹配以进行尺寸推荐。进行了广泛的用户体验研究。通过半结构化焦点小组访谈和问卷调查对开发的应用程序进行了经验测试,以验证结果并获得进一步的见解。这项研究为从时尚电子商务的单个图像生成的低成本尺寸推荐提供了重大创新。通过将人体测量结果与服装的个性化推荐进行匹配,可以增强在线服装的购物体验。

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