human/demo/faceid

Human Face Recognition: FaceID

faceid runs multiple checks to validate webcam input before performing face match
Detected face image and descriptor are stored in client-side IndexDB

Workflow

• Starts webcam
• Waits until input video contains validated face or timeout is reached
  • Number of people
  • Face size
  • Face and gaze direction
  • Detection scores
  • Blink detection (including temporal check for blink speed) to verify live input
  • Runs antispoofing optional module
  • Runs liveness optional module
• Runs match against database of registered faces and presents best match with scores

Notes

Both antispoof and liveness models are tiny and designed to serve as a quick check when used together with other indicators:

• size below 1MB
• very quick inference times as they are very simple (11 ops for antispoof and 23 ops for liveness)
• trained on low-resolution inputs

Anti-spoofing Module

• Checks if input is realistic (e.g. computer generated faces)
• Configuration: human.config.face.antispoof.enabled
• Result: human.result.face[0].real as score

Liveness Module

• Checks if input has obvious artifacts due to recording (e.g. playing back phone recording of a face)
• Configuration: human.config.face.liveness.enabled
• Result: human.result.face[0].live as score

Models

FaceID is compatible with

• faceres.json (default) perfoms combined age/gender/descriptor analysis
• faceres-deep.json higher resolution variation of faceres
• mobilefacenet alternative model for face descriptor analysis