Face recognition

Face recognition is a biometric method of identifying an individual by comparing the captured live or digital image with a set of stored images.

​Face matching to persons of interest on premises in real time

Real-time video surveillance against photo gallery and watch list databases

Real-time alarm generation to reduce security threats

Ability to create a large database of gallery models and match people against that database.

Accurate checking of portrait characteristics for gender, age, pose deviation, exposure and face geometry.

The algorithm is flexible. It can be installed and configured locally, in the cloud, or in a hybrid manner. It is compatible with Mac, Windows, or Linux. The platform can be extended to mobile devices via the SAFR mobile app running on MacOS or Android.

​The algorithm identifies or verifies a person from a digital image or video frame.

It compares selected facial features from the image to a database of faces.

The process begins with face detection, where the algorithm identifies an object as a “face” and detects it in the image or video.

The algorithm then decides whether the “face” is someone known or unknown and establishes its identity.

CAELUM uses a highly accurate algorithm powered by machine learning. It has fast processing, high-scale performance, and is capable of identifying and comparing millions of faces in real time.

The algorithm has been tested and proven by NIST and compared with more than eighty algorithms submitted by companies and institutions around the world, achieving an enviable level of precision and performance that determined its leading position in a category of excellence.