Abstract
Measuring body sizes accurately and rapidly for optimal garment fit detection has been a challenge for fashion retailers. Especially for apparel e-commerce, there is an increasing need for digital and convenient ways to obtain body measurements to provide their customers with correct-fitting products. However, the currently available methods depend on cumbersome and complex 3D reconstruction-based approaches. In this paper, we propose a novel smartphone-based body size measurement method that does not require any additional objects of a known size as a reference when acquiring a subject’s body image using a smartphone. The novelty of our proposed method is that it acquires measurement positions using body proportions and machine learning techniques, and it performs 3D reconstruction of the body using measurements obtained from two silhouette images. We applied our proposed method to measure body sizes (i.e., waist, lower hip, and thigh circumferences) of males and females for selecting well-fitted pants. The experimental results show that our proposed method gives an accuracy of 95.59% on average when estimating the size of the waist, lower hip, and thigh circumferences. Our proposed method is expected to solve issues with digital body measurements and provide a convenient garment fit detection solution for online shopping.
Highlights
As the world becomes more technology-driven and consumers prioritize convenience for their shopping and lifestyles, smartphones serve important roles in diverse areas of our daily lives
We focused on body measurements for pants, which clothing customers have fit issues with the most [10]
Equation (8) is used in the background removal algorithm: Isilhouette = Isubject − Ibackground where Isubject is the grayscale image with the subject, Ibackground is the grayscale image of the background, and Isilhouette is the silhouette image of the subject
Summary
As the world becomes more technology-driven and consumers prioritize convenience for their shopping and lifestyles, smartphones serve important roles in diverse areas of our daily lives. As the fashion e-commerce industry continues its growth, it is forecasted to be facing a trilliondollar problem in the form of returns [1] This industry challenge shows the potential of smartphones to provide a convenient and rapid fit detection method to solve the sales and return issues in the industry. The convenience and affordable price point of mobile scanners in comparison with their larger, more expensive counterparts (e.g., 3D full-body scanners) offer a high feasibility of adopting such technology by the fashion industry [2] This shows that the potential of multi-million dollar profits can be saved by reducing the probability of online returns [8]. Body measurements of three areas, including the waist, lower hip and thigh, are used in this study
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