• Ms. Chaitra S
• K S Vinay
• M C V Ugandhar
• Manit S Hegde
• Nakul V

This project introduces a novel approach to real-time emotion detection and visualization, leveraging facial and hand landmarks. Through the integration of the MediaPipe library for landmark detection and OpenCV for webcam interfacing, the system captures live video input and extracts landmarks crucial for emotion analysis. A machine learning model, trained on a dataset collected via webcam input, predicts emotions based on these landmarks. The system dynamically overlays corresponding emoji images onto the webcam feed, providing users with intuitive visual representations of their emotions. Augmenting the visualizations are textual annotations, further elucidating the detected emotions. Results showcase the system's efficacy in accurately detecting and visualizing emotions in real-time. The project's contributions extend to enhancing user engagement and comprehension, with potential applications in human-computer interaction and affective computing domains.

Facial Expression Recognition, Human-Computer Interaction, Machine Learning, Real-time Processing, Avatar Generation, Emotion Recognition, Data Collection, Model Training.

"Implementation paper on facial expression to avatar", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.d664-d669, May-2024, Available :http://www.jetir.org/papers/JETIR2405375.pdf

"Implementation paper on facial expression to avatar", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. ppd664-d669, May-2024, Available at : http://www.jetir.org/papers/JETIR2405375.pdf