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Facial Recognition Check-in

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Coming soon

Facial Recognition Check-in is available for early access. Contact Support for more information. 

 

Contents

 

About Facial Recognition Check-in

Facial Recognition Check-in enables touchless check-in at the kiosk for visitors who have authorized Eptura Visitor to use their photograph for identification.

We use the Microsoft Azure AI Face service to generate algorithms that analyze human faces in images. Learn more: https://learn.microsoft.com/en-us/az...rview-identity

How does it work?

Ahead of a visit, a visitor can submit a photo of their face via remote registration and authorize its use for identification purposes. 

The remote registration process requests access to the device's camera and prompts the visitor to take a photo of their face. When uploaded, they can authorize the image to be used for facial recognition via the Use for AI facial recognition check-in button. The button is toggled on by default.

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The photo is then used to create a model of their face, which is referenced when they arrive and check in at the kiosk.

When the visitor arrives, they simply face the kiosk, and their live image is referenced against the stored photos to verify their identity and check them in. Any additional check-in flow then continues as usual.

If facial recognition fails to verify the visitor (for example, due to a poor-quality photo), they can check in via traditional methods. Learn more: Photo requirements

 

Compatibility

  • iOS: version tbc
  • Android v8 and above

Facial recognition is not supported by Visitor kiosks running in a web browser.

 

How to enable Facial Recognition Check-in

The following settings in Eptura Visitor are required to enable Facial Recognition Check-in:

 

Photo requirements

Submitted photographs must be high-quality, straight-on portrait images:

  • Photos must be clear and sharp - not blurry, pixilated, distorted, or damaged.
  • Photos must not be edited to remove facial blemishes or alter facial appearance.

Faces might not be recognized under the following conditions:

  • Images with extreme lighting, for example, severe back lighting.
  • Obstructions that block one or both eyes.
  • Differences in hair type or facial hair.
  • Changes in facial appearance.
  • Extreme facial expressions.

Learn more: https://learn.microsoft.com/en-us/az...t-requirements