Overview
Facial recognition systems map facial features from a photograph or video and compare them against a database of known faces to find a match.
The Process
- Face Detection: Locating a face within the image.
- Face Alignment: Normalizing the face's position and scale.
- Feature Extraction: Converting the face into a numerical representation (face embedding).
- Face Matching: Comparing the embedding against a database using similarity metrics.
Key Technologies
- Deep Convolutional Neural Networks: Used to learn highly discriminative facial features.
- Siamese Networks: Often used for one-shot verification tasks.
Ethical and Privacy Concerns
Facial recognition is a controversial technology due to concerns about surveillance, privacy, and algorithmic bias (e.g., lower accuracy for certain demographic groups).