Introduction
Amazon Rekognition Face Liveness is a managed AWS service that uses advanced machine learning to determine if a detected face is from a live person instead of a spoofed image, video, or mask.
When paired with the Amplify FaceLivenessDetector component, it becomes straightforward to integrate liveness verification directly into your web or mobile application with minimal configuration.
Alongside liveness detection, Amazon Rekognition CompareFaces enables precise face matching between a captured image and one or more stored reference images in a face collection.
For optimal performance, a collection should contain at least two or three different faces to ensure accurate comparison results and avoid false positives.
By combining these services, you gain several advantages over traditional face verification methods:
- Real-time liveness verification prevents spoof attacks using photos, videos, or masks.
- High-accuracy face matching through Rekognition CompareFaces, with similarity scoring to identify the best match.
- Simple front-end integration with Amplify UI components, reducing development time.
- No need for custom ML model training, as AWS handles the model lifecycle.
- Scalable storage for reference images using Amazon S3.
- Seamless authentication integration with Amazon Cognito for user management.
- Serverless deployment with AWS Lambda, reducing infrastructure costs.
- Audit-friendly — API calls and results can be logged for compliance purposes.
With these capabilities, Rekognition Face Liveness combined with Amplify FaceLivenessDetector and CompareFaces delivers a secure, accurate, and developer-friendly solution for identity verification in modern applications.
