Publications

Displaying 1 - 25 of 53

Face Analysis Technology Evaluation: Age Estimation and Verification

May 29, 2024

Author(s)

Kayee Hanaoka, Patrick J. Grother, Mei Lee Ngan, Joyce Yang, George W. Quinn, Austin Hom

Face Analysis Technology Evaluation (FATE) Part 10: Performance of Passive, Software-based Presentation Attack Detection (PAD) Algorithms

September 19, 2023

Author(s)

Mei Lee Ngan, Patrick J. Grother, Austin Hom

This report quantifies the accuracy of passive purely software-based face presentation attack detection (PAD) algorithms operating on conventional 2D imagery of various presentation attack instruments (PAI). The algorithms were submitted to the

Face Analysis Technology Evaluation (FATE) Part 11: Face Image Quality Vector Assessment: Specific Image Defect Detection

September 19, 2023

Author(s)

Joyce Yang, Patrick J. Grother, Mei Lee Ngan, Kayee Hanaoka, Austin Hom

Ongoing Face Recognition Vendor Test (FRVT) Part 9a: Face Recognition Verification Accuracy on Distinguishing Twins

September 22, 2022

Author(s)

Kayee Hanaoka, Mei Lee Ngan, Patrick J. Grother, Austin Hom

Face Recognition Vendor Test (FRVT) Part 4A: MORPH - Utility of 1:N Face Recognition Algorithms for Morph Detection

July 29, 2022

Author(s)

Mei Lee Ngan, Patrick J. Grother, Kayee Hanaoka

This report is a part of a series of studies on the topic of face morphing, its relevance and implications as a vulnerability to automated face recognition, and methods to aid in detecting morphs. Expanding on concepts introduced in a study conducted by

Face Recognition Vendor Test (FRVT) Part 7: Identification for Paperless Travel and Immigration

July 13, 2021

Author(s)

Patrick J. Grother, Austin Hom, Mei Lee Ngan, Kayee Hanaoka

One-to-many biometric search systems are discussed in their role of positive and negative identification - the former refers to the expectation that person in a probe sample is present in the database (as in access to an office) while the latter presumes

Ongoing Face Recognition Vendor Test (FRVT) Part 6B: Face recognition accuracy with face masks using post-COVID-19 algorithms

November 30, 2020

Author(s)

Mei L. Ngan, Patrick J. Grother, Kayee K. Hanaoka

This is the second of a series of reports on the performance of face recognition algorithms on faces occluded by protective face masks commonly worn to reduce inhalation and exhalation of viruses. This is a continuous study is being run under the Ongoing

Ongoing Face Recognition Vendor Test (FRVT) Part 6A: Face recognition accuracy with masks using pre- COVID-19 algorithms

July 24, 2020

Author(s)

Mei L. Ngan, Patrick J. Grother, Kayee K. Hanaoka

This is the first of a series of reports on the performance of face recognition algorithms on faces occluded by masks, run under the Ongoing Face Recognition Vendor Test (FRVT) executed by the National Institute of Standards and Technology (NIST). This

Face Recognition Vendor Test (FRVT) Part 4: MORPH - Performance of Automated Face Morph Detection

March 6, 2020

Author(s)

Mei L. Ngan, Patrick J. Grother, Kayee K. Hanaoka, Jason M. Kuo

The FRVT MORPH test provides ongoing independent testing of prototype face morphing attack detection (MAD) technologies. The evaluation is designed to obtain commonly measured assessment of morph detection capability to inform developers and current and

Face Recognition Vendor Test Part 3: Demographic Effects

December 19, 2019

Author(s)

Patrick J. Grother, Mei L. Ngan, Kayee K. Hanaoka

Face Recognition Vendor Test (FRVT) Part 2: Identification

September 13, 2019

Author(s)

Patrick Grother, Mei Ngan, Kayee Hanaoka

This report updates and extends NIST Interagency Report 8238, documenting performance of new face recognition algorithms submitted for evaluation to NIST in November 2018. The algorithms implement one-to-many identification of faces appearing in two-

Ongoing Face Recognition Vendor Test (FRVT) Part 2: Identification

November 27, 2018

Author(s)

Patrick J. Grother, Mei L. Ngan, Kayee K. Hanaoka

This report documents performance of face recognition algorithms applied to the one-to-many identification of faces appearing in portrait images. The primary dataset is comprised of 26.6 million reasonably well controlled live photos of 12.3 million

Tattoo Recognition Technology - Evaluation (Tatt-E): Performance of Tattoo Identification Algorithms

October 31, 2018

Author(s)

Mei L. Ngan, Patrick J. Grother, Kayee K. Hanaoka

NIST performed a large scale empirical evaluation of tattoo recognition algorithms. The test leveraged large operational datasets comprised of tattoo images from law enforcement databases, enabling evaluation with enrollment database sizes of up to 100,000

The Text Recognition Algorithm Independent Evaluation (TRAIT)

December 15, 2017

Author(s)

Afzal A. Godil, Patrick J. Grother, Mei L. Ngan

The report describes and presents the results for text detection and recognition (TRAIT) evaluation in support of forensic investigations of digital media. These im- ages are of interest to NISTs partner law enforcement agencies that seek to employ text

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