This project was an exploration into modern computer vision techniques, specifically focusing on facial detection and recognition. The goal was to build a simple, working prototype that could identify and label faces in images or video streams.
Technologies Used
The solution leveraged powerful, open-source libraries to handle the complex mathematical models required for accurate recognition:
- **[Specific ML Library, e.g., Python/OpenCV/dlib]:** Used for initial face detection and landmark identification.
- **[Specific ML Model, e.g., Pre-trained model]:** For embedding faces into a high-dimensional space for comparison.
- **JavaScript/HTML:** For the web interface (if you built a web demo).
Key Findings and Challenges
Discuss the performance of the model, how well it generalized to new faces, and any challenges faced (e.g., lighting, angles, occlusions).