Emotion Detection and Emoji Display
Author : Shreya Vivek Chunarkar and Dr. Lenina SVB
Abstract :
Emotion recognition through facial expressions significantly enhances Human-Computer Interaction by allowing machines to interpret and respond to human emotions in real-time. This paper presents a robust Emotion Detection and Emoji Display System that utilizes live facial input from a camera to analyze facial features. The system identifies emotions such as happiness, sadness, anger, surprise, and neutrality by employing pre-trained recognition models. Detected emotions are then visualized using corresponding animated or static emojis on the user interface, fostering intuitive user interactions.
The model is built on advanced computer vision techniques and a lightweight deep learning framework, ensuring high accuracy and low latency in emotion classification. Focused on user-centric design, the system promotes real-time performance, scalability, and seamless integration into interactive applications. Experimental findings demonstrate the system's effectiveness in various lighting conditions and face orientations. The potential applications of this research are extensive, spanning across education, mental health monitoring, social robotics, gaming, and diverse digital communication platforms.
Keywords :
Emotion Detection, Facial Expression Recognition, Computer Vision, Deep Learning, Convolutional Neural Networks (CNN), Real-Time Processing, Human–Computer Interaction (HCI) etc.
