NEC’s Video Face Recognition Technology ranks first in NIST Testing

NEC Corporation has announced that NEC’s face recognition technology achieved the highest performance evaluation in the recent Face in Video Evaluation (FIVE, *1) testing performed by the U.S. National Institute of Standards and Technology (NIST) (*2). Results were released in NIST’s Interagency Report 8173: Face In Video Evaluation (FIVE) Face Recognition of Non-Cooperative Subjects.

NEC’s face recognition technology took first place for the fourth consecutive time following the 2009 Multiple Biometric Grand Challenge (MBGC 2009), 2010-2011 Multiple Biometrics Evaluation (MBE 2010-2011), and 2013 Face Recognition Vendor Test (FRVT 2013).

Video face recognition technology identifies the faces of moving subjects in real-time as they walk naturally without stopping in front of a camera. The benefits of high-speed video analysis enabled by this technology include the prevention of potential incidents through detection of suspicious individuals and recognition of individuals at the gateways of critical facilities.
Using video images from standard cameras for face recognition requires highly-advanced techniques when compared to still images. This is because images are greatly influenced by environmental conditions, such as camera location, image quality, lighting and subject size, in addition to the behavior of a subject, including walking speed, face direction and sight line.
To achieve reliable face recognition of a video image, NEC developed feature point extraction technology that enables enhanced face recognition to a level where an individual can be identified with high precision from within a group, even if their face is partially hidden, or the image is taken from different angles. NEC’s face recognition technology also uses deep learning technologies for face matching to increase accuracy to a level where an individual can be identified by a low resolution face image captured by a distant camera.

Evaluation examples from the NIST FIVE testing
•      Entry-exit management at an airport passenger gate
Tests were conducted to recognize one individual at a time as they walk through an area without stopping or acknowledging the camera. NEC’s face recognition technology won first place with a matching accuracy of 99.2%. The error rate of 0.8% is less than one-fourth of the second place error rate.
•      Detection of suspicious individuals at an indoor stadium
Tests were conducted with an individual situated far from the camera with their face direction changing frequently. NEC’s face recognition technology won first place with an error rate half that of the second place error rate.