Cotton T-Shirt Size Estimation Using Convolutional Neural Network
Online shopping has become popular due to its convenience and potential cost savings. However, clothing size cannot be accurately estimated, particularly when buying shirts. Many shoppers provide size choices but with inaccurate fits. To assist users in selecting the correct size when purchasing t-s...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
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| Series: | Engineering Proceedings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-4591/92/1/44 |
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| Summary: | Online shopping has become popular due to its convenience and potential cost savings. However, clothing size cannot be accurately estimated, particularly when buying shirts. Many shoppers provide size choices but with inaccurate fits. To assist users in selecting the correct size when purchasing t-shirts online, we estimated shirt size using calculated upper body dimensions. Computer vision algorithms, including YOLO, PoseNet, body contour detection, and a trained convolutional neural network (CNN) model were employed to estimate shirt sizes from 2D images. The model was tested using images of 30 participants taken at a distance of 180–185 cm away from a Raspberry Pi camera. The estimation accuracy was 70%. Inaccurate predictions were attributed to the precision of body measurements from computer vision and image quality, which needs to be solved in further studies. |
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| ISSN: | 2673-4591 |