VER-ID PERSON SDK

Easily add biometric verification to any digital process.

Streamlined registration & fast authentication ensures user acceptance; liveness detection prevents "spoofing".

Ideal for Time & Attendance applications where Ver-ID Person can be configured to run with multi-camera time clocks and no-PIN/no-badge use cases.

Ver-ID is selected by developers who understand the importance of choosing technology that ‘learns’ users, creating an ever-improving UX, and which can run standalone on mobile devices, anticipating the full breadth of use cases for biometrics across their organizations.

THE VER-ID ADVANTAGE

Accurate

Offers a best-in-class accuracy curve, achieving the lowest false rejection rate for any target. Our SDK also makes it simple to adjust the balance between security and convenience.

On-Board Liveness

Our proprietary randomized-pose methodology defeats spoofing without degrading the user experience. You can adjust sensitivity levels to the security needs of individual use case.

Future Proof

Our deep patent portfolio, uniquely experienced team, commitment to R&D and singular focus on face technology make Applied Recognition the easy choice when selecting a face recognition technology partner.

Learns Users

Our patented composite face signature architecture allows "proven-good" images to be added to a user's profile after registration, enabling ever-improving accuracy and tolerance to "appearance drift".

Platform Independent

Ver-ID is available in versions for most common server and mobile platforms, enabling support for the broadest variety of use cases. ARI currently supports LINUX, Windows, iOS, Android and Cordova.

Mobile Advantage

Ver-ID runs within the constraints of a mobile device, enabling use cases where server-only technologies can’t meet specs. As biometrics becomes routine for more processes, most organizations will require facerectech that can run standalone on mobile devices.

HOW IT WORKS

Isolate & Identify. Our software intelligently compensates for real-world image quality issues, enabling a wider range of applications. It then identifies & maps the core geometry of the human face, creating a one-of-a-kind signature, to easily distinguish different users.
Create a 3D Model. Our core benchmark setting algorithms are designed to match images taken with the face in different spatial positions. By creating a detailed dimensional model quickly and accurately - even on mobile devices - Ver-ID is able to preserve accuracy in a broad range of "real world" conditions.
Compare Images. The final stage in a successful biometric authentication is matching the user's registered signature with the captured image. We do this using a hybrid model that blends deterministic methodologies with AI-grounded methods. Our technology detects subtle commonalities and distinctions to enable simultaneous ‘low false positive’ with ‘low false negative’ rates.

ON-BOARD LIVENESS

Applied Recognition uses head position (pose left/right/up) as well as advanced anti-spoofing techniques to validate that a person – and not a video or picture – is attempting to authenticate.

Our 3D technology consistently excels in “white hat” tests, denying access to high quality spoofing attempts including images and videos of registered users.

Standard 3D Face

Straight-on pose with 3D human face geometry.

Live Motion

Landmarks move in 3D with a real person.

Image Detected!

Spoof attempted with a printed image or mobile device. 2D geometry detected and halted! Even video spoofing attempts are thwarted by randomized head-rotation guidance.

FUTURE-PROOF BIOMETRICS

Schedule a demonstration to see Ver-ID Person's performance for yourself.

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Address

700 Third Line
Oakville, Ontario
Canada L6L 4B1

Contacts

sales@appliedrec.com

Links

Github Repository

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