FaceMe® SDK, a cross-platform facial recognition engine, is uniquely positioned to integrate edge-based AI facial recognition into a wide range of IoT and AIoT solutions. FaceMe® SDK is optimized to run on most hardware configurations, from high-end workstations to low-power chipsets typically used in IoT devices. It is compatible with Windows, Linux, Android and iOS systems.
FaceMe® SDK is top ranked in both NIST FRVT 1:1 and 1:N. In 1:N, FaceMe® provides up to 99.83 TAR in VISA Border investigation mode, which is ideal for use cases like border check and eKYC. In 1:1 WILD photo, FaceMe® reached 96.98% TAR (with FMR at 1E-5), ideal for use cases like security and surveillance.
No. 1 in 1:N
No. 6 when incl. China & Russia Vendors
VISA Border 1:N
Investigation Mode/1.6M DB
No. 1 in 1:1
No. 6 when incl. China Vendors
Wild Photo 1:1
FMR: 1E-5 (0.00001)
Based on machine learning and deep neural network, FaceMe® has an accuracy rate (TAR, True Acceptance Rate) of 99.83% at 10-4 FAR. It ranks amongst the most precise and fastest facial recognition engines in NIST's Face Recognition Vendor Test (FRVT).
Multiple anti-spoofing technologies provide highly secure, accurate liveness detection to protect against biometric fraud, e.g. replay attack and print attack. FaceMe® supports anti-spoofing with mainstream 3D cameras as well as 2D cameras on phones and tablets.Watch Video
FaceMe®'s updated algorithm provides the ability to accurately recognize a person's identity with up to 98% accuracy rate even if they are wearing a mask. It enables instantaneous and hygienic touchless biometric recognition.
Facial recognition can enhance security, identify potentially fraudulent activities and help loss prevention. FaceMe®’s cross-platform SDK and flexible architecture enable an easy deployment in any environment.
FaceMe® supports a variety of operating systems and AI inference engines. It is designed to run on mainstream processors and is optimized to take advantage of GPU / VPU hardware acceleration. FaceMe®’s flexible and scalable architecture provides hardware and software developers the tools to create customized facial recognition solutions and experiences.