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Smart Face Recognition API

Our face recognition API adds robust algorithms for image processing to your tech infrastructure for higher accuracy. It allows you to gather actionable insights from images and video data as well as count the presence of human faces with precision.
Facial detection and automatic landmark identification

Core Functionality

  • Facial detection and automatic landmark identification from visual data for crowds and individuals
  • Split-second search for identification and verification of an unlimited number of faces
  • A multi-stage approach to facial feature detection
  • Precise recognition technique due to high tolerance to complex illumination variations and partial occlusions (single and multiple objects)
  • Face recognition API comparison feature – 30k faces per second – analyzing, comparing, and verifying features
  • Real-time head pose detection API for human-machine interaction
  • Facial emotion recognition API to analyze and determine a person’s internal emotional state
High Identification Precision

Identification Precision Specs

  • 1:1 (Verification) and 1:N (Identification)
  • Recommended dimension: 112 px
  • Face rotation: up to 45⁰
  • Occluded detection – 35%
  • Number of devices – unlimited (more optical instruments drive more processing capabilities)
  • Interpupillary distance: >25 px
  • Ratio of false acceptances < 0.0001%
  • Configurable threshold range

Demo for API Face Recognition

Benefits For Your Business

Leverage the power of hi-tech fueled by Artificial Intelligence and Computer Vision.
Face Biometric Authentication
Biometric samples to estimate the shared facial features.
Face Recognition
Attribute Detection
Attribute detection for commonly used landmarks.
Biometric Data Storage
Data extraction for personalized biometrics and binary storage.
IP Camera Compatibility
API supports any optical instrument.
Pose Estimation
Quick And Accurate Face Detection
System enhancement for better recognition capabilities.
Cross-camera Image Processing.
Tracking with multiple cameras for a crowded scenery.

Why Prefer Our API?

Looking to ramp up identification accuracy? We’ve got your back. Apply our API to a range of scenarios with ready-to-use models.
  • Improved Productivity
    Easy To Use
    Robust face detection with concise code integration.
  • Privacy First
    Processed locally, your data stays safe and exclusive.
  • Strong ML team
    Multi Faces
    Face detection of any complexity - individuals, crowds, and groups.
  • Multi Devices
    Our flexible solution covers multiple devices, including mobile and drones.
Our API will enhance your face identification app.

How Our Clients Use Our Products

Intelligent Time Attendance Management System

The client is a US-based health center.

They wanted to prevent transferring the coronavirus through touched surfaces. The health center decided to introduce a new system for employee check-ins and -outs. Our biometric face identification time attendance software reduced the spread of the disease.

The solution is equipped with touchless authentication and helps minimize health risks. Thus, health workers can easily enter and leave facilities as well as report working hours.

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Face Detection SDK for Surveillance System

The client is a famous treasure gallery.

They were looking for a face SDK to prevent art crime and protect cultural assets. To improve security surveillance, we customized our facial SDK for their security system.

The detection system recognizes the worker based on their facial landmarks. The results are then compared against the employee database. If the system recognizes the employee, they enter the facility. The solution also enhanced robbery and burglary prevention by 73%.

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DL Anti-Spoofing

Deep Learning To Prevent Anti-Spoofing

Our client owns an E-commerce tech business and provides cloud-based services to conduct financial operations.

The client needed a facial recognition software API to avert spoofing attacks.
The solution is a deep learning-based model to prevent both static and digital image attacks. Our team took over the whole pipeline of model training and inference. We also enabled the import of the final neural network so that the client could use it from Java.

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