Passive and Active Liveness

Describing how passive and active liveness works.

The objective of the Liveness check is to verify the authenticity and physical presence of an individual in front of the camera. In the passive Liveness check, it is sufficient to capture a user's face while they look into the camera. Conversely, the active Liveness check requires the user to perform an action such as smiling, blinking, or turning their head. While passive Liveness is more user-friendly, active Liveness may be necessary in some situations to confirm that the user is aware of undergoing the Liveness check.

In our Mobile or Web SDKs, you can define what action the user is required to do. You can also combine several actions into a sequence. Actions vary in the following dimensions:

• User experience,

• File size,

• Liveness check accuracy,

• Suitability for review by a human operator or in court.

In most cases, the Selfie action is optimal, but you can choose other actions based on your specific needs. Here is a summary of available actions:

Passive Liveness

Selfie	A short video, around 0.7 sec. Users are not required to do anything. Recommended for most cases. It offers the best combination of user experience and liveness check accuracy.
One shot	Similar to “Simple selfie” but only one image is chosen instead of the whole video. Recommended when media size is the most important factor. Hard to evaluate for a spoofing by a human, e.g., by an operator or in a court.
Scan	A 5-second video where a user is asked to follow the text looking at it. Recommended when the longer video is required, e.g., for subsequent review by a human operator or in a court.

Active Liveness

Smile Blink Tilt head up Tilt head down Turn head left Turn head right

A user is required to complete a particular gesture within 5 seconds. Use active liveness when you need a confirmation that the user is aware of undergoing a Liveness check. Video length and file size may vary depending on how soon a user completes a gesture.

To recognize the actions from either passive or active Liveness, our algorithms refer to the corresponding tags. These tags indicate the type of action that a user is performing within a media. For more information, please read the Media Tags article. The detailed information on how the actions, or, in other words, gestures are called in different Oz Liveness components is here.