Face verification is a huge achievement in computer vision. Its applications stretch from social tagging and image processing to real-time surveillance systems. Face verification involves identifying an individual’s biometrics using multiple facial features like lips, nose, and color. The capabilities of a biometric face verification service play a vital role in different tasks like:
- Head pose tracking
- Behavior analysis
- Face recognition
- Face verification
The technology allows system users to determine the location and size of a face in an image or video. Some unique features of face verification technology include:
- Real-time surveillance
- Security, privacy, and accuracy of biometric data
- The ability to identify and convey a person’s feelings
Face verification techniques usually involve methods like eigenvalue disintegration and eigenvectors for simple implementation and accurate recognition.
Key Features and Capabilities
A face verification solution is intended for creating end-user web and mobile applications that complete identity verification on personal gadgets, including tablets, mobiles, and PCs, in systems such as:
- Payments
- Digital onboarding
- Shops self-checkout
- Online banking
- Media sharing and social networks
- Government e-services
Face verification systems are based on proprietary algorithms, which are designed to offer advanced face localization, matching and face liveness detection, and face enrolment. They deliver these functionalities using strong image-processing algorithms based on neural networks. The main features are:
- Face image quality determination: High-quality checks based on ISO 19794-5 standards are used during face liveness detection and enrolment. This ensures that only high-quality face templates are stored in the database on the device.
- Advanced checks for automatic digital onboarding: For certain usage scenarios, key features like dark glasses, hat detection, and age estimation can be optionally enabled.
- Presentation attack detection: Different attack types can trick an unsupervised biometric face verification system. A well-designed face verification algorithm can prevent this type of security breach. It achieves this by being able to determine whether a face image in footage belongs to an actual individual. The liveness detection can take place in a completely passive mode. No cooperation is needed from the user. In addition to passive checks, when no cooperation is needed from the user, the active mode evaluates the response of the user to complete certain tasks or actions like head movements and blinking.
- Security and privacy: Face images and biometric templates can be safely and securely stored and used on the server, end-user device, or both. This depends on the implication. Face images are only needed for the creation of templates and face liveness detection. That means they can be disposed of immediately after completing these operations.
Do you want to get a real feel of these features and capabilities? You can find face verification demos here. Check them to discover more.
