Virtual Trial Room with Computer Vision and Machine Learning
This addresses the issue of uncertainty in online purchases for customers and vendors, though it is incremental as it builds on existing models like DECA.
The paper tackled the problem of high return rates in online shopping for wearable products by developing a Virtual Trial Room platform that uses computer vision and machine learning to generate a 3D model of a user's head from a single 2D image and superimpose 3D glasses models, allowing customers to check fit and suitability virtually.
Online shopping has revolutionized the retail industry, providing customers with convenience and accessibility. However, customers often hesitate to purchase wearable products such as watches, jewelry, glasses, shoes, and clothes due to the lack of certainty regarding fit and suitability. This leads to significant return rates, causing problems for both customers and vendors. To address this issue, a platform called the Virtual Trial Room with Computer Vision and Machine Learning is designed which enables customers to easily check whether a product will fit and suit them or not. To achieve this, an AI-generated 3D model of the human head was created from a single 2D image using the DECA model. This 3D model was then superimposed with a custom-made 3D model of glass which is based on real-world measurements and fitted over the human head. To replicate the real-world look and feel, the model was retouched with textures, lightness, and smoothness. Furthermore, a full-stack application was developed utilizing various fornt-end and back-end technologies. This application enables users to view 3D-generated results on the website, providing an immersive and interactive experience.