Face recognition solution

IFace SDK is a specialized image processing software library. It offers state-of-the-art technology for detection of faces in static and streamed images, face image quality evaluation and feature points detection, and unrivaled face recognition.

Typically, while processing an image stream, it enables to detect and trace face(s) in the images based on pre-set parameters (e.g. minimal / maximal eye distance), evaluate the pertinent characteristics and extract the chosen frames for further processing.

IFace SDK uses a set of features designed to satisfy facial image quality requirements established by ISO/IEC 19794-5 standard and ICAO (International Civil Aviation Organization) specifications.

Powerful features and benefits

Key features

Thanks to implementing the newest findings in the field of pattern recognition and image processing, IFace SDK is tremendously fast while assuring the highest accuracy in the detection of faces and their features. This allows for the simultaneous detection and tracking of multiple faces in one image (stream) instance.

IFace SDK’s simplicity and speed meet even the most demanding business needs. Just choose and implement your strategy in finding and tracking faces, feed IFace SDK with your images or image stream content, and receive everything you need in real-time.

With every face found you can get a series of qualitative and quantitative parameters, which allow for further processing. For example, to crop out facial images with the highest achievable quality.

IFace SDK offers a stable high-speed and accurate algorithm for face matching.

Supported Operating Systems

Windows: 2000, XP, Vista, 7, 8, Server; Linux: Red Hat, Debian; Android

API

C/C++

Connectors / Wrappers

.NET, Java

Sample Applications

C++, .NET, Java

Image Formats

All standard image formats – jpg, png, bmp, tif

Template Size

300 B

Want to know more?

Download datasheet
face recognition, face tracking, face detection

IFace SDK is designed:

  • to assure convenient support for self-service and assisted enrollment scenarios
  • to enable quality evaluation of pre-enrolled facial images as per normative requirements
  • to support face tracking and evaluation scenarios in real-time image processing
  • to enable high speed face recognition solutions.

Any questions?

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