FaceVACS Technology

enables clients to develop new face recognition and facial image analysis applications

Cognitec's products incorporate state-of-the-art technologies relevant to working with facial images, in particular deep learning, computer vision, and pattern recognition technologies. Algorithmic optimization since 1995 has resulted in superior independence from facial variances such as pose, mimic, age variance, different hair styles, glasses or temporary lighting changes.

The B12 algorithm achieved superior results in the 2018 NIST FRVT 1:1 with visa photos, and most recently, in the 2019 FRVT: Identification (1:N). The FaceVACS Engine also includes the A16 matching algorithm, featuring a much smaller memory footprint suitable for the development of face recognition applications for mobile devices.

Technology made in Germany
Version 9.4 highlights
  • incorporates matching algorithm B12
  • NIST-acclaimed matching accuracy and speed
  • available for Windows, Linux, Android and macOS
How to purchase our technology

Contact the sales team or send an email with your contact details and application requirements.


  • powerful face localization and face tracking on images and video streams
  • industry-leading matching algorithms for enrollment, verification and identification
  • accurate portrait characteristics check for gender, age, pose deviation, exposure, glasses, eyes closed, uniform lighting detection, unnatural color, image and face geometry
  • ISO 19794-5 full frontal image type checks and formatting as required for ePassports
  • supports multiple algorithms to work with two-dimensional intensity data, or two-dimensional data and corresponding range data (3D data)

Engine licensing

Cognitec’s FaceVACS Engine enables clients worldwide to develop new face recognition applications. It provides a clear and logical API for easy integration in other software programs.

Cognitec provides the FaceVACS Engine through customized software development kits, with a set of functions and modules specific to each use case and computing platform, and based on tailored software licensing agreements. Such specific use cases include: image quality check, verification for document issuance, and verification for access control.

Programming and development

  • advanced face recognition APIs: C++, Java, Microsoft .NET, BioAPI 2.0 Verification Engine (C API)
  • documented examples for main use cases and customized implementations
  • tools for biometric evaluations: e.g. generation of identification match lists, similarity matrix data

Android development

  • supports the development of portable face recognition applications
  • used in handheld devices to capture photos and compare them to image databases on the device or central systems
  • adds security to login and authentication procedures