id3 Face SDK¶
id3 Face SDK is a cross-platform library aimed at system integrators willing to quickly add face detection, recognition, PAD and/or analysis capabilities to their products. It is available as a Software Development Kit (SDK) offering a comprehensive interface to simplify integration of the library on servers, desktops/laptops, mobile and edge devices.
This user guide is intended to help developers quickly get started with the SDK, covering the setup, basic operations, advanced features, and troubleshooting tips to ensure a smooth integration process.
Features¶
id3 Face SDK offers the following features and benefits:
Top performance facial biometrics, AI powered
Optimized for AI hardware, including GPU acceleration, for fast operation
Robust human face detection and tracking in digital images or video frames
Small facial features template (268 bytes or 140 bytes)
Ultra-fast face template matching in one-to-one comparison and one-to-many search modes
Multiple face analysis functionalities: landmarks estimation, pose estimation, mask detection, etc.
Facial attributes determination for ICAO compliant portraits
Face image quality assessment
Accurate passive liveness detection methods to protect against biometric fraud, e.g. presentation attacks with photos and videos
Compact library designed to run on most hardware configurations from high-end workstations to low-power edge devices
Compatible with Windows, Linux, MacOS, Android and iOS operating systems
Simple and comprehensive programming interface in various languages
Applications¶
Public Safety
Border Control
Mobile apps
ID Management
Banking & Payment
Automobile & Transportation
Healthcare
Editions¶
id3 Face SDK is available in the following editions:
Edition |
Platforms |
Description |
|---|---|---|
Server |
Windows, Linux or macOS |
Full-featured edition generally used for server or desktop-based applications.
Enables one-to-many search mode.
|
Mobile |
Android, iOS |
This edition is for mobile applications. |
Biometric Performance¶
The overall accuracy of a facial recognition system may vary according to a number of factors such as:
Quality of the camera system,
Lighting conditions,
Facial pose variations,
Population under test,
etc.
Performance metrics¶
False non match rate (FNMR) is the proportion of mated comparisons below a threshold set to achieve the false match rate (FMR) specified. FMR is the proportion of impostor comparisons at or above that threshold. Since FMR and FNMR is in inverse proportion to each other, choosing the operational threshold is a trade-off between system security and user convenience.
NIST FRVT evaluation¶
The Face Recognition Vendor Test (FRVT) was initiated by the National Institute of Standards and Technologies (NIST) in February 2017. It is aimed at measurement of the performance of automated face recognition technologies applied to a wide range of civil, law enforcement and homeland security applications including verification of visa images, de-duplication of passports, recognition across photojournalism images, and identification of child exploitation victims.
The latest report of the FRVT can be found [here](https://pages.nist.gov/frvt/reports/11/frvt_11_report.pdf).
The face encoder 9A of this SDK corresponds to the id3_008 submission.
A complete report card can also be found [here](https://pages.nist.gov/frvt/reportcards/11/id3_008.html), showing among things, the evolution of our face recognition technology over the years.
Support¶
Should you encounter any issues or have questions while using the SDK, our dedicated support team is ready to assist you. Visit our Customer Portal Page (https://customer.id3.eu) or contact us directly at support@id3.eu for help.