The project aims to develop a robust and accurate system that can automatically detect and localise key facial features, such as eyes, nose, mouth, and eyebrows, in real-time from images or video frames. Facial recognition has gained significant attention in computer vision and pattern recognition due to its potential applications in various domains, such as biometrics, surveillance, and human-computer interaction. In this project, we propose a facial characteristics recognition system using the popular open-source libraries, Mediapipe and OpenCV. The system utilises the Mediapipe library to detect and localise key facial landmarks, such as eyes, nose, mouth, and eyebrows, from input images or video frames, and then employs OpenCV for further image processing and feature extraction. The extracted facial characteristics are then used for facial recognition tasks, such as gender classification, age estimation, and emotion recognition.
- Features easy to use and intuitive UI for users
- Detects and segments the face, iris, eyebrows and mouth of the user
- Makes use of Flask as a backend to integrate the model
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