TeeVision: Customize and Buy Your Fits
In today’s digital era, interactive and personalized user experiences play a critical role in enhancing customer engagement and satisfaction in the e-commerce industry. Traditional online shopping platforms often lack customization features, making it difficult for users to visualize and personalize products according to their preferences. To address this challenge, this project focuses on developing an interactive and customizable clothing platform using modern web technologies such as JavaScript and React.js. In the modern digital world, user experience has emerged as a game-changer in every industry, especially when it comes to online shopping and product personalization. One such limitation for users is the inability to customize clothing items in real-time on most e-commerce platforms. Manually browsing products without personalization options can be restrictive and less engaging, particularly for users who want unique and tailored designs. To address this issue, the Customize Your Fit Project is designed and implemented using JavaScript, React.js, and advanced animation libraries. The goal of the project is to develop a system that allows users to customize their outfits interactively and visualize changes in real time before making a purchase, thus enhancing user experience and engagement. This project focuses on enabling users to design and personalize their clothing items by selecting colors, textures, and styles, and then proceed to purchase them seamlessly through the platform. This project aims to develop an interactive system that mimics real-time product customization—allowing users to modify clothing designs, explore different styles, and make informed purchasing decisions. The system reduces the gap between imagination and reality by providing a dynamic and immersive interface, ensuring a smooth and engaging shopping experience.
Authors
- Vasu Pandey, Somansh Choudhary, Poorab Sahu, P. Madhu Mayank Babu, Mr. Manoj Kumar Singh
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-05-02
- DOI
- https://doi.org/10.5281/zenodo.19972174
- Primary Topic
- 3D Shape Modeling and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00