Enterprise-grade facial detection and identity verification with anti-spoofing, multi-face tracking, and sub-200ms database matching against 1M+ identities.
Visylix Face Recognition combines deep-learning face detection with a specialized embedding engine for reliable identity verification at enterprise scale. The system processes multiple faces per frame, performs liveness analysis to prevent spoofing attempts, and matches faces against databases containing over one million identities in under 200 milliseconds. It estimates age range, gender, and facial expressions while handling challenging conditions like low light, partial occlusion, varied angles, and high crowd density.
Core capabilities of the Face Recognition model.
Simultaneously identifies and tracks dozens of faces in single frames, even in crowded environments with overlapping subjects and rapid movement.
Layered liveness checks guard against printed photos, screen replays, and 3D mask attacks through depth estimation and texture analysis.
99.7% true-positive verification rate on standard evaluation sets at a 1-in-a-million false-accept threshold.
Searches galleries of one million+ identities in under 200 milliseconds with GPU-accelerated vector indexing.
Provides age range and gender estimation for retail, hospitality, and public safety applications.
Identifies neutral, happy, surprised, and distressed expressions for customer experience monitoring.
Maintains recognition accuracy in challenging lighting conditions including backlit, dim, and mixed-illumination environments.
Handles yaw, pitch, and roll variations up to 60 degrees with minimal accuracy degradation for real-world camera placements.
Real-world applications for Face Recognition.
Replaces badges and PINs with face-based entry verification in under one second at turnstiles, doors, and secure zones.
Notifies staff immediately when high-value guests or flagged individuals appear on camera through integrated dispatch systems.
Automates time-and-attendance for large workforces, eliminating manual timesheets and buddy-punching across multiple facility entrances.
Scans live feeds against missing-person and suspect databases with confidence scores and audit trails for investigative support.
Identifies returning customers and analyzes demographic patterns to optimize store layouts, staffing, and targeted marketing campaigns.
Performance and deployment details.
Add Face Recognition to your video pipeline in minutes.
Assign the model to specific cameras with zone definitions and sensitivity settings through the web UI or API.
The model processes video frames in real time, generating structured detection events with bounding boxes and metadata.
Receive instant alerts via webhooks, trigger automated workflows, or query detections through the REST API.
See how Face Recognition is applied across different sectors.
Explore other computer vision capabilities.
Talk to our team to see this model in action on your video feeds.