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Search Publications by: P. Jonathon Phillips (Fed)

Displaying 201 - 225 of 242

Privacy Operating Characteristic for Privacy Protection in Surveillance Applications

October 1, 2005

Author(s)

P J. Phillips

With the mass deploy of cameras, concern has risen about protecting a person's privacy as he goes about his daily life. Many of the cameras are installed to perform surveillance tasks that do not require the identity of a person. In the context of

Linear and Generalized Linear Models for Analyzing Face Recognition Performance

August 17, 2005

Author(s)

J. R. Beveridge, Geof H. Givens, Bruce A. Draper, P. Jonathon Phillips

This paper introduces linear models (LM), generalized linear models (GLM), and generalized linear mixed models (GLMM) for analyzing performance of face recognition algorithms. These three statistical techniques are applied to analyzing the affect of

2003 U.S. Government Biometrics Workshop: Overview and Summary

April 1, 2003

Author(s)

D M. Blackburn, R Lazarick, Calvin Miles, P. Jonathon Phillips, Fernando L. Podio

Overview and summary of the 2003 U.S. Government Biometrics Workshop, 9 April 2003. This document, and other associated information, can be found in the U.S. Government Biometrics Workshops area of the Biometrics Catalog, http://www.biometricscatalog.org.

The NIST Human ID Evaluation Framework

April 1, 2003

Author(s)

Ross J. Micheals, Patrick J. Grother, P J. Phillips

In this paper, we investigate the utility of static anthropometric distances as a biometric for human identification. The 3D landmark data from the CAESAR database is used to form a simple biometric consisting of distances between fixed rigidly connected

Face Recognition Vendor Test 2002 Performance Metrics

March 1, 2003

Author(s)

Patrick Grother, Ross J. Micheals, P. Jonathon Phillips

We present the methodology and recognition performance characteristics used in the Face Recognition Vendor Test 2002. We refine the notion of a biometric imposter, and show that the traditional measures of identification and verification performance are

Face Recognition Vendor Test 2002: Evaluation Report

March 1, 2003

Author(s)

P J. Phillips, Patrick J. Grother, Ross J. Micheals, D M. Blackburn, Elham Tabassi, M Bone

The Face Recognition Vendor Test (FRVT) 2002 is an independently administered technology evaluation of mature face recognition systems. FRVT 2002 provides performance measures for assessing the capability of face recognition systems to meet requirement for

Dependence Characteristics of Face Recognition Algorithms

January 1, 2002

Author(s)

Andrew L. Rukhin, Patrick J. Grother, P J. Phillips, Stefan D. Leigh, E M. Newton, Nathanael A. Heckert

Nonparametric statistics for quantifying dependence between the output rankings of face recognition algorithms are described. Analysis of the archived results of a large face recognition study shows that even the better algorithms exhibit significantly

Transformation, Ranking, and Clustering for Face Recognition Algorithm Performance

January 1, 2002

Author(s)

Stefan D. Leigh, Nathanael A. Heckert, Andrew L. Rukhin, P J. Phillips, Patrick J. Grother, E M. Newton, M Moody, K Kniskern, S Heath

The performance of face recognition algorithms is recently of increased interest, although to date empirical analyses of algorithms have been limited to rank-based scores such a cumulative match score and receiver operating characteristic. This paper

Meta-Analysis of Face Recognition Algorithms

March 1, 2001

Author(s)

P J. Phillips, E M. Newton

To obtain a quantitative assessment of the state of automatic face recognition, we performed a meta-analysis of performance results of face recognition algorithms in the literature. The analysis was conducted on 24 papers that report identification

Computational and Performance Aspects of PCA-Based Face Recognition Algorithms

January 1, 2001

Author(s)

H Moon, P. Jonathon Phillips

Principal component analysis (PCA) based algorithms form the basis of numerous algorithms and studies in the psychological and algorithmic face recognition literature. PCA is a statistical technique and its incorporation into a face recognition algorithm

The FERET Evaluation Methodology for Face-Recognition Algorithms

October 1, 2000

Author(s)

P J. Phillips, H Moon, S A. Rizvi, P J. Rauss

Two of the most critical requirements in support of producing reliable face-recognition systems are a large database of facial images and a testing procedure to evaluate systems. The face Recognition Technology (FERET) program has addressed both issues

Image Processing and Recognition - Mixture of Experts for Classification of Gender, Ethnic Origin, and Pose of Human Faces

July 1, 2000

Author(s)

S Gutta, J Huang, P. Jonathon Phillips, H Wechsler

In this paper we describe the application of mixtures of experts on gender and ethnic classification of human faces, and pose classification, and show their feasibility on the FERET database of facial images. The FERET database allows us to demonstrate

Introduction to Evaluating Biometric Systems

February 21, 2000

Author(s)

P J. Phillips, Alvin F. Martin, Charles L. Wilson, Mark A. Przybocki

Biometric technology has the potential to provide secure access using user characteristics, biometric signatures, that cannot be lost, stolen, or easily duplicated. However, the actual performance of many existing systems is unknown. Potential users of