AI-Based Virtual Trial Room for E-Commerce

Abstract

The rapid growth of e-commerce has transformed the way consumers purchase fashion products; however, the inability to physically try on garments remains a significant limitation, often leading to uncertainty, dissatisfaction, and high product return rates. This project presents an AI-Based Virtual Trial Room for E-Commerce, a web-based application designed to enhance the online  shopping experience by enabling users to visualize clothing items on their own images before making a purchase. The proposed system leverages advanced Artificial Intelligence, Computer Vision, and Deep Learning techniques, integrating tools such as MediaPipe for real-time pose detection and OpenCV for image processing and garment overlay. By detecting key body landmarks and analyzing user posture, the system accurately aligns and fits selected apparel onto the user’s uploaded image, ensuring a realistic and personalized virtual try-on experience. The platform supports multiple clothing categories including topwear, bottomwear, outerwear, traditional wear, and accessories, specifically tailored for men’s fashion. Additionally, the application features an interactive catalog, real-time filtering, and a responsive user interface with both light and dark modes, enhancing usability and accessibility. The system aims to reduce return rates, improve customer confidence, and increase engagement by providing a convenient, efficient, and immersive shopping solution. Overall, this project demonstrates the potential of AI-driven virtual try-on systems to revolutionize the digital retail industry by bridging the gap between physical and online shopping experiences.