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Trueface Achieves Top 3 Global Rank on NIST FRVT for Speed

Search 1 billion identities in 1 second ⚡️

Searches so fast, you can feel it.

We are proud to report that Trueface has achieved the third-highest global ranking on the NIST FRVT 11 competition in the template match speed category. When it comes to biometric identity verification, Trueface has the number one fastest software in the West. Trueface executes a biometric template comparison in as little as 186 nanoseconds. To put that into perspective, that is 800,000 times faster than the blink of an eye.

What exactly is template match time?

Face recognition algorithms work by generating a biometric template from an input face image. The biometric template is a fixed-length list of numbers that mathematically describe certain attributes of the face. When two of these biometric templates are provided to the algorithm, it compares the templates to determine the similarity, and thus the probability that the identity of the two templates are the same. The time taken to perform this comparison is the match time.

Why is a fast template match speed critical?

The above example describes the process of 1 to 1 identity verification. In a 1 to 1 verification situation, we only compare two biometric templates against each other to obtain a similarity score.

However, more often than not, we are performing 1 to N identity verification. In these situations, we do not simply compare two biometric templates against each other, but instead, compare a biometric template against a database of potentially millions of biometric templates. In such cases, the template match comparison must be performed millions of times in order to determine if there was a single match in the database. Often, this search operation needs to be performed at least 30 times a second for a single 30 fps video camera. Once you add multiple camera feeds or extended video to the equation, it’s easy to see why match speed is so critical.

If we were to search every frame of a seven-minute video against a database of 1 million identities, Trueface would complete that search in 39 minutes. It would take our closest American competitor 1 hour and 7 minutes.

In certain scenarios, 28 minutes of extra time can make all the difference.

How does the Trueface algorithm perform on different hardware?

The Trueface matching algorithm has been optimized for speed on various platforms ranging from server-grade CPUs to embedded devices. The following table summarizes the 1 to N search benchmarks on various hardware platforms:

Source: https://docs.trueface.ai/Benchmarks-0b648f5a0cb84badb6425a12697a15e5

To highlight a few of the key points in the table above, the Trueface algorithm can search through 100 million identities on a single 10th generation Intel i-7 CPU in 873 ms. This can be scaled to achieve 1 billion identities per second if using a CPU cluster or alternatively a single CPU with many threads (ex. AMD Threadripper). On the embedded end, the Trueface algorithm can search through 1 million identities in 35 ms on an NVIDIA Jetson Xavier, and 192 ms on a Raspberry Pi 4. Hence, the Trueface algorithm can meet real-time requirements for large collections sizes even on embedded devices.

Disclaimer: Results shown from NIST do not constitute an endorsement of any particular system, product, service, or company by NIST. For more information, visit https://www.nist.gov/programs-projects/face-recognition-vendor-test-frvt-ongoing

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