Mindbox facial recognition software searches an existing database of faces and compares them with the faces detected in the scene to find a match. Face Recognition detects faces in the camera’s field of view – as many as 15 at the same time – and matches them against faces previously stored in the database. Anti-spoofing is provided through “liveness” testing without the need for a stereo or 3D camera. Faces can be enrolled in the database from existing still images or from the video camera itself.

Facial recognition in Face Intellect is powered by deep neural networks (DNN). Algorithms of the new generation are free of recognition issues which were typical for the previous “non-DNN” generation.

Neural network algorithms are basically AI, artificial intelligence — powerful machine learning-based techniques, which emulate how the human brain operates. DNN is trained on a huge dataset with labeled faces to map a face to a numerical vector representation. Once the network has been trained, it can compare any faces, even ones it has never seen before.

Facial recognition with DNN offers top-quality predictions regardless of the camera angle, lighting, hairstyle, facial expression, glasses, or other variations. Actually, modern algorithms work even better than humans can do.

Step 1: Face Intellect automatically picks out faces in the video feed from cameras.

Step 2: It compares them to a database, such as an employee access list or a blacklist.

Step 3: When it determines a given degree of similarity (high or low), it triggers the system to lock or unlock a door, send an alert to security personnel, and so on.

Step 4: When used in access control, facial recognition can also be part of a Time and Attendance system.

Search video footage

You can quickly find faces that match a picture, video image, or photo-fit and jump to event video.

Collect statistics

Use Face Intellect as a people counter to get unique and total visitor numbers, find out their gender and age, and get reports for business analysis.