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Information Technology

Biometrics

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Displaying 451 - 475 of 804

Image specific error rate: A biometric performance metric

August 20, 2010
Author(s)
Elham Tabassi
Image-specific false match and false non-match error rates are defined by inheriting concepts from the biometric zoo. These metrics support failure mode analyses by allowing association of a covariate (e.g., dilation for iris recognition) with a matching

Recognizing people from dynamic and static faces and bodies: Dissecting identity with a fusion approach

August 12, 2010
Author(s)
Alice J. O'Toole, P. Jonathon Phillips, Samuel Weimer, Dana A. Roark, Julianne Ayadd, Robert Barwick, Joseph Dunlop
The goal of this study was to evaluate human accuracy at identifying people from static and dynamic presentations of faces and bodies. Participants matched identity in pairs of videos depicting people in motion (walking or conversing) and in \best" static

Report on the Evaluation of 2D Still-Image Face Recognition Algorithms

June 17, 2010
Author(s)
Patrick J. Grother, George W. Quinn, P J. Phillips
The paper evaluates state-of-the-art face identification and verification algorithms, by applying them to corpora of face images the population of which extends into the millions. Performance is stated in terms of core accuracy and speed metrics, and the

Quantifying How Lighting and Focus Affect Face Recognition Performance

June 13, 2010
Author(s)
J. R. Beveridge, David Bolme, Bruce A. Draper, Geof H. Givens, Yui M. Lui, P. Jonathon Phillips
Recent studies show that face recognition in uncontrolled images remains a challenging problem, although the reasons why are less clear. Changes in illumination are one possible explanation, although algorithms developed since the advent of the PIE and

An Other-Race Effect for Face Recognition Algorithms

May 13, 2010
Author(s)
P J. Phillips, Alice J. O'Toole, Abhijit Narvekar, Fang Jiang, Julianne Ayadd
Psychology research has shown that human face recognition is more accurate for faces of one�s own race than for faces of other races. In recent years, interest in accurate computer-based face recognition systems has spurred the development of these systems

FRVT 2006: Quo Vidas Face Quality

May 10, 2010
Author(s)
P J. Phillips, J. R. Beveridge, Geof H. Givens, Bruce A. Draper, David Bolme, Yui M. Lui
This paper summarizes a study of how three state-of-the-art algorithms from the Face Recognition Vendor Test 2006 (FRVT 2006) are effected by factors related to face images and the people being recognized. The recognition scenario compares highly

Multiple Encounter Dataset I (MEDS-I)

May 9, 2010
Author(s)
Craig I. Watson
In December, 2008, the FBI provided MITRE with an extract of submissions of deceased persons. The submissions contain face images of subjects with multiple encounters over time. The type 10 records (face and SMT) are mostly frontal or near frontal face

Significance Test in Operational ROC Analysis

April 5, 2010
Author(s)
Jin Chu Wu, Alvin F. Martin, Raghu N. Kacker, Robert C. Hagwood
To evaluate the performance of fingerprint-image matching algorithms on large datasets, a receiver operating characteristic (ROC) curve is applied. From the operational perspective, the true accept rate (TAR) of the genuine scores at a specified false

Quantifying How Lighting and Focus Affect Face Recognition Performance

February 16, 2010
Author(s)
P J. Phillips, J. R. Beveridge, Bruce A. Draper, David Bolme, Geof H. Givens, Yui M. Lui
Recent studies show that face recognition in uncontrolled images remains a challenging problem, although the reasons why are less clear. Changes in illumination are one possible explanation, although algorithms developed since the advent of the PIE and

Biometrics Systems Include Users

December 16, 2009
Author(s)
Mary F. Theofanos, Ross J. Micheals, Brian C. Stanton
Where do biometrics come from? The “canonical” standard (Wayman) biometric system model includes the biometric presentation and a biometric sensor but not the user themselves. Having this model facilitates having shared vocabulary and abstraction for