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.

翻译：在线购物已彻底改变零售行业，为客户带来便利性与可及性。然而，由于无法确定穿戴类产品（如手表、珠宝、眼镜、鞋履及服装）的贴合度与适配性，消费者在购买时往往犹豫不决。这导致退货率居高不下，为消费者和商家均带来困扰。为解决此问题，本研究设计了一个基于计算机视觉与机器学习的虚拟试衣间平台，使消费者能够便捷地检验产品是否贴合自身需求。为实现该功能，本研究采用DECA模型从单张二维图像生成人工智能驱动的头部三维模型。随后，将基于真实尺寸定制的眼镜三维模型叠加至头部模型并进行适配。为还原真实视觉效果，模型通过纹理、明暗与平滑度处理进行精细化修饰。此外，本研究利用多种前后端技术开发了全栈应用程序，使用户能够在网站端查看三维生成结果，获得沉浸式交互体验。