1:1 Face Matching
Experience our AI driven face matching matching service that prevents your business from being attacked by fraudsters and cyber-criminals. We are an iBeta certified organisation and provide customised face matching solutions to our clients
Facia’s Matching Services
1:1 matching matches a single image with another image in real-time. This technology is ideal for applications that require accurate identification of a person based on a single image, such as verifying a person’s identity document.
1:N matching system scans over 1 million images in under a second. Our service is scalable and can handle databases of millions of images, making it an ideal solution for large-scale industries.
Image-to-video matching system is designed to match an image with a real-time video feed to detect fraud. This technology is ideal for applications that require tracking a person’s movements in real-time.
The video-to-video mechanism matches a video with another video feed in real time. This is ideal for applications that require tracking a person’s movements across different locations.
Benefits of Face Matching Technology
Stop Repeated Scams
Our AI-driven face matching service alerts you in case of any fraudulent biometric activity and highlights additional information about the attackers.
Face matching adds an extra layer of security to protect your business from fraudulent activities. It can compare a live individual’s facial biometric to an existing image (such as an identity document) or a database of images.
Boost Your Customers’ Trust
Increase the trust of your customers by incorporating our advanced face matching service for 1:1 and 1:N solutions.
Frequently Asked Questions
1:1 Face Matching refers to the process of comparing a probe image of a face with a specific image in a database to determine if they are same individuals. It's primarily used for verification purposes, such as during logins or access controls, ensuring that the person is real.
While 1:1 Verification (or Authentication) involves confirming the identity of a subject by comparing their face with a known image, 1:N Authentication (Identification) compares the subject's face against multiple images in a database to identify who they might be. In essence, verification confirms identity, while identification determines it.
1:N (or one-to-many) matching involves comparing a probe image with multiple images in a database to find potential matches. It's especially useful in identification scenarios, like identifying a person of interest in surveillance footage by comparing their face against a database of known individuals.
False negatives occur when the facial recognition system fails to match a probe image to a similar image in the database, even though they represent the same individual. This can lead to genuine users being denied access. But systems like Facia, minimizes such occurrences for optimal user experience.
False positives arise when a system incorrectly matches a probe image to a different person's image in the database. Facia's advanced 1:1 algorithms are designed to reduce false positives, ensuring that unauthorized individuals don't gain access to secure systems or areas.
FRVT, or Facial Recognition Vendor Test, is a series of evaluations conducted by NIST (National Institute of Standards and Technology) to assess the performance of facial recognition algorithms. It provides an industry-standard benchmark, helping users gauge the accuracy and reliability of different facial recognition solutions.