Basic Recommendations for VeriLook Surveillance Usage

Face recognition accuracy of VeriLook Surveillance heavily depends on the quality of a face image. Image quality during enrollment is important, as it influences the quality of the face template.

There are some basic recommendations and constraints when using face recognition applications based on VeriLook Surveillance SDK.

Cameras and images

• Similar quality cameras are recommended for both enrollment and identification. Using the same camera model is even better. Enrollment from photo is also possible if it conforms to other requirements on this page.
• 40 pixels is the recommended minimal distance between eyes for a face on image or video stream to perform face template extraction. 75 pixels or more recommended for better face recognition results. Note that this distance should be native, not achieved by resizing an image.
• 1 MegaPixel or better camera resolution is recommended for face enrollment and recognition. Make sure that native resolution is provided by a camera, as some cameras or webcams may scale up native images to higher resolution without image quality improvement.
• Check for mirrored face images, as recognition will fail if a face was enrolled from a mirrored image, and later a non-mirrored face image is used for recognition (or vice versa). This happens as some cameras can be configured to produce mirrored images or may even produce them by default, and different cameras or configurations may be used during enrollment and identification. We recommend to use face images with uniform orientation – all images within a system should be either native or mirrored, but not mixed between each other.
• Use several images during enrollment, as it improves facial template quality which results in improvement of recognition quality and reliability.

Lighting

Controlled lighting conditions are recommended:

• Direct frontal or diffused light allows equal lighting distribution on each side of the face and from top to bottom with no significant shadows within the face region.
• Avoid glares on face skin or glasses that are produced by some types of illumination.

Face posture

The VeriLook Surveillance face recognition engine has certain tolerance to face posture:

• head roll (tilt) – ±180 degrees (configurable);
  • ±15 degrees default value is the fastest setting which is usually sufficient for most near-frontal face images.
• head pitch (nod) – ±15 degrees from frontal position.
  • The head pitch tolerance can be increased up to ±25 degrees if several views of the same face that covered different pitch angles were used during enrollment.
• head yaw (bobble) – ±45 degrees from frontal position (configurable).
  • ±15 degrees default value is the fastest setting which is usually sufficient for most near-frontal face images.
  • 30 degrees difference between a face template in a database and a face image from camera is acceptable.
  • Several views of the same face can be enrolled to the database to cover the whole ±45 degrees yaw range from frontal position.

Face quality recommendations for enrollment

• Neutral face expression during enrollment is recommended, as non-neutral face expression may affect the accuracy of recognition.
• Several images with different appearance variants are recommended for enrollment to assure the quality of recognition in the situations when part of face is covered with glasses or hair:
  • Eyeglasses – separate enrollments with and without glasses will assure the best recognition quality for both cases.
  • Hair style – some hair styles may cover parts of face, thus hairpins or other means of holding hair off the face are recommended during enrollment.
  • Facial hair style changes may require additional enrollments, especially when beard or moustache is grown or shaved off.

Memory and Performance Constraints During Face Tracking

• Memory usage. VeriLook Surveillance consumes about 10 MB of memory per minute when tracking one face at a speed of 10 frames per second. The consumed memory is released after the face disappears from a frame.
• Multiple faces in a frame. If multiple faces are visible in a frame, tracking performance falls down.
• Minimal frame rate. It is recommended to retrieve at least 10 frames per second from a camera. If less than 10 frames are captured, face tracking feature may be not available.

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