Liveness¶
The liveness algorithm enables LUNA PLATFORM to detect presentation attacks. A presentation attack is a situation when an imposter tries to use a video or photos of another person to circumvent the recognition system and gain access to the person’s private data.
There are the following general types of presentation attacks:
Video Replay Attack. A video of another person is used
Printed Photo Attack. One or several photos of another person are used
Printed Mask Attack. An imposter cuts out a face from a photo and covers his face with it
3D Mask Attack. A silicone or plastic mask is used
Liveness check results¶
The liveness algorithm uses a single image for processing and returns the following data:
Liveness probability [0..1]. The parameter shows the probability of a live person being present in the image, i.e. it is not a presentation attack. In general, the estimated probability must exceed the theoretical threshold of 50%. The value may be increased according to your business rules
Image quality [0..1]. The parameter describes the integral value of image, facial, and environmental characteristics. In general, the estimated quality must exceed the theoretical threshold of 50%. The threshold may be increased according to the photo shooting conditions
See the “Liveness” section of the OpenAPI documentation for details.
APCER (Attack Presentation Classification Error Rate) — the rate of undetected attacks where algorithms identified the attack as a real person
BPCER (Bona Fide Presentation Classification Error Rate) — the rate of incorrectly identified people where algorithms identified real people as fakes
Additional request parameters¶
You can specify the device OS type in the “OS” field of the “meta” object in the request:
IOS
ANDROID
DESKTOP
UNKNOWN
The parameter can decrease the overall error rate.
Requirements¶
There are certain requirements for image quality and face alignment that must be met to get correct results.
Face requirements¶
Yaw and pitch angles are no more than 20 degrees in either direction
The roll angle no more than 30 degrees in either direction
The minimal distance between the eyes ~90 degrees (it is forbidden to set the value lower than 80 degrees)
Single face in the image. It is recommended to avoid several faces being present in the image.
No sunglasses
Capture requirements¶
No blur (increases BPCER)
No texture filtering (increases APCER)
No spotlights on the face and close surroundings (increases BPCER)
No colored light (increases BPCER)
The face in the image must not be too light or too dark (increases BPCER)
No fish-eye lenses
Image requirements¶
Horizontal and vertical oriented images of 720p and 1080p
Minimal image height: 480
No or minimal image compression. The compression highly influences liveness algorithms