FaceVACS Performance

Various tests by independent organizations have demonstrated that Cognitec's face recognition technology is industry-leading in terms of recognition accuracy and speed.

FRVT 2002 At the Face Recognition Vendor Test 2002, conducted by the National Institute of Standards and Technology (NIST), Cognitec's face recognition software exhibited the best performance among all participants for large-scale verification, identification, as well as watch list scenarios.

FRVT 2006 The latest NIST test, conducted in 2006, confirms the outstanding performance of Cognitec's technology. Of 22 companies and research institutes, only Cognitec and 10 other participants could complete the large-scale tests, and only Cognitec and one other company could deliver measurements in four different test scenarios for still images and 2D/3D data.

The results also demonstrated that Cognitec exceeded the goal specified by the so-called Face Recognition Grand Challenge, or FRGC, which was to prove increased recognition performance by an order of magnitude as compared to results measured during FRVT 2002. Cognitec again delivered top performance in the majority of the tests, especially with regard to common real-world scenarios (low resolution imagery).

Subsequent to January 2006, the cut-off date for algorithm submission for FRVT 2006 test purposes, Cognitec has continued to enhance the already robust operational performance of its existing systems through measured and focused R&D efforts. Specifically, Cognitec's latest search engine, known as B4T8, exhibits considerably enhanced performance relative to strong lighting variations over the search engine tested through FRVT 2006. Using one of the publicly available image databases, the FERET Duplicate I, the false rejection rate has decreased from 3.7% to 2.6% (at a false acceptance rate of 0.1%), depicting a marked relative improvement of almost 30%. On other images, with more challenging light conditions, improvements of up to 80% were reached.

Disclaimer: FRVT results do not constitute endorsement of any particular system by the Government. Complete test results can be downloaded at www.frvt.org.

You can download the results as pdf here 'results as pdf'

The 'Duplicate I' test involves the following subsets of the FERET database: a gallery including 1196 images of 1183 persons and a probe set of 722 images of 242 persons. The lower curve is based on the FaceVACS engine used during FRVT2006, the upper curve uses the current FaceVACS engine version B4T8.

Neither of Cognitec's algorithms is specifically optimized or trained on databases used for tests, like the FERET database. Training and optimization is only done on internal proprietary databases which do not contain data from test databases. Consequently, Cognitec's test results can be generalized to similar unknown set of data.

MBGC 2009

MBGC is a project conducted by the U.S. National Institute of Standards and Technology (NIST) with the purpose to foster progress in face and iris recognition technology. The Multiple Biometric Grand Challenge is not considered an independent evaluation test as the MBGC participants report their results to NIST themselves, a circumstance not allowing a practically relevant comparison of the capabilities of different face recognition technologies.

For the MBGC, NIST defines several so-called challenge problems (involving comparing face images and videos taken under various, more or less difficult conditions), and prospective participants are invited to apply their technology to those problems and to submit their results, in terms of comparison scores. All image data used in the challenge problems are public, enabling the participants to tune their algorithms to the image data.