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AI-based Face Recognition

Mindbox Is A Leading Developer Of Intelligent Video Management And Physical Security Information Management Software. Since 2020, The Company Has Been Creating Disruptive Technologies That Push The Safety & Security Industry Forward In The Space Of Computer Vision, AI/ML, Mixed Reality, And Data Center.

Key Features

  • Facial recognition accuracy over 99.5% on public standard data sets
  • Face recognition in real-time, depending on resources
  • Easily enroll faces from still or video images
  • Zero gender or racial bias through model training with millions of faces from datasets from around the world
  • Anti-spoofing technology ensures the system cannot be fooled by a photo or video image
  • Detect matches with faces in the database and provide alerts
  • Create a log of faces in the scene for later investigation
  • REST API for building into applications and devices
  • Search for similar faces from a single camera or across multiple cameras
  • In use in thousands of cameras for access control, VIP greeting, shoplifter, and unwanted person applications

Deep learning algorithms

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.

How Face IntelliVision Works

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.


Facial Recognition accuracy as high as 99.6% on public standard data set.

Facial Recognition – Accurate and Fast

Using AI and deep learning, Mindbox face recognition has achieved accuracy benchmarks better than industry leaders like Google and Facebook. It scores the following accuracy in the leading public test databases – LFW: 99.6%, YouTube Faces: 96.5%, MegaFace (with 1000 people/distracters): 95.6%.


Face recognition in real time or off-line.

Recognition is available in both real-time and off-line modes and enrollment is available from both video and still images. Facial recognition is achieved by analyzing multiple images per face and can be achieved in around 0.5 seconds depending on resources.


For OEM partners and application builders.

Face Recognizer is available with a REST API/SDK for OEM partners and application builders. Easy integration of alerts is achieved through HTTP/JSON and open architecture.