Emotion Aware Webpage Portfolio

Abstract: The rapid evolution of user-centric design has led to the emergence of emotionally responsive digital interfaces. This project presents an Emotion-Aware Webpage Portfolio, a personalized web system that dynamically adapts its presentation based on the user's emotional state. Using real-time facial expression recognition powered by a browser-based machine learning model (TensorFlow.js), the system classifies emotions such as happiness, sadness, anger, surprise, and neutrality from live webcam input. These detected emotions are then mapped to adaptive UI components, enabling modifications in color themes, textual tone, animations, and interactive elements. The goal is to enhance user engagement by creating a portfolio interface that reacts intuitively to user affect. The project demonstrates that integrating affective computing with web technologies can significantly improve user experience, accessibility, and immersion. The results highlight strong potential for emotion-driven design in future web applications.

Keywords: Emotion detection, Affective computing, Web-based portfolio, Real-time facial expression recognition, TensorFlow.js, Adaptive user interface, Human-computer interaction, User experience personalization, Computer vision, Emotion-aware design