Face Recognition

Face recognition is a biometric technology that identifies or verifies a person by extracting mathematical features from their facial image and comparing those features against a reference database.

How It Works

Modern face recognition follows four steps:

1. Detection. A convolutional neural network locates every face in a video frame.
2. Alignment. The face is rotated and normalized to a canonical pose.
3. Embedding. A deep neural network converts the face into a numeric vector (usually 128–512 dimensions) that is unique to that person.
4. Matching. The vector is compared to stored embeddings using distance metrics (cosine or Euclidean) to produce a match score.

The whole pipeline runs in milliseconds per face and scales to millions of enrolled identities.

Why It Matters

Face recognition solves problems that manual ID checks and card-based access never could:

• Touchless authentication for access control, attendance, and boarding.
• Proactive security — watchlist matches alert operators the moment a person of interest appears.
• Customer insight (with consent) — VIP recognition in retail, recurring visitor analytics.
• Forensic search — find every appearance of a suspect across weeks of recorded video in seconds.

IncoreSoft's AI face recognition module achieves up to 99.35% accuracy, handles 200 faces per frame, and is GDPR-ready out of the box.

Use Cases

• Access control — door unlock, turnstile entry, data center security
• Attendance systems — shift clock-in for factories and hospitals
• Safe City — watchlist matching for wanted persons or missing people
• Retail — VIP recognition and repeat-visitor analysis
• Airports and transit — passenger verification at boarding gates

Frequently Asked Questions

How accurate is face recognition in the real world?

In calibrated deployments with good camera placement and lighting, top engines reach 99%+ accuracy on single-face reads. Accuracy drops with occlusions, extreme angles, or low light, which is why production systems use multi-frame voting and fallback rules.

Is face recognition GDPR-compliant?

It can be, when deployed with lawful basis, purpose limitation, data minimization, retention controls, and operator access auditing. IncoreSoft's engine supports on-premise deployment so biometric data never leaves your infrastructure.

What's the difference between face detection and face recognition?

Detection finds that there is a face in the image. Recognition identifies whose face it is. Every recognition pipeline starts with detection.