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Information Technology

Biometrics

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  • Published Date
Displaying 176 - 200 of 412

Dictionary-based Face Recognition from Video

December 10, 2012
Author(s)
P J. Phillips, Yi-Chen Chen, Vishal M. Patel, Rama Chellappa
The main challenge in recognizing faces in video is effec- tively exploiting the multiple frames of a face and the accompanying dynamic signature. One prominent method is based on extracting joint appearance and behavioral features. A second method models

Preliminary Studies on the Good, the Bad, and the Ugly Face Recognition Challenge Problem

November 26, 2012
Author(s)
P J. Phillips, J. R. Beveridge, David Bolme, Bruce A. Draper, Yui M. Lui
Face recognition has made significant advances over the last twenty years. State-of-the-art algorithms push the performanceenvelope to near perfect recognition rates on many face databases. Recently, the Good, the Bad, and the Ugly (GBU) face challenge

Demographic Effects on Estimates of Automatic Face Recognition Performance

November 22, 2012
Author(s)
P J. Phillips, Alice J. O'Toole, Xiaobo An, Joseph Dunlop
The intended applications of automatic face recognition systems include venues that vary widely in demographic diversity. Formal evaluations of algorithms do not commonly consider the effects of population diversity on performance. We document the effects

A Grassmann Manifold-based Domain Adaptation Approach

November 20, 2012
Author(s)
P J. Phillips, Jingjing Zheng, Ming-Yu Liu, Rama Chellappa
Domain adaptation algorithms that handle shifts in the distribution between training and testing data are receiving much attention in computer vision. Recently, a Grassmann manifold-based domain adaptation algorithm that models the domain shift using

The Good, the Bad, and the Ugly Face Challenge Problem

November 20, 2012
Author(s)
P J. Phillips, J. R. Beveridge, Bruce A. Draper, Geof H. Givens, Alice J. O'Toole, David Bolme, Joseph Dunlop, Yui M. Lui, Hassan A. Sahibzada, Samuel Weimer
The Good, the Bad, & the Ugly Face Challenge Problem was created to encourage the development of algorithms that are robust to recognition across changes that occur in still frontal faces. The Good, the Bad, & the Ugly consists of three partitions. The

Comparing Face Recognition Algorithms to Humans on Challenging Tasks

October 17, 2012
Author(s)
P J. Phillips, Alice O'Toole, Xiaobo An, Joseph Dunlop, Vaidehi Natu
We compared face identifcation by humans and machines using images taken under a variety of uncontrolled illumination conditions in both indoor and outdoor settings. Natural variations in a person's day-to-day appearance (e.g., hair style, facial

Cross-View Action Recognition via a Transferable Dictionary Pair

September 12, 2012
Author(s)
P J. Phillips, Jingjing Zheng, Zhuolin Jiang, Rama Chellappa
Discriminative appearance features are effective for recognizing actions in a fixed view, but generalize poorly to changes in viewpoint. We present a method for view- invariant action recognition based on sparse representations using a transferable dictio-

An Exploration of the Operational Ramifications of Lossless Compression of 1000 ppi Fingerprint Imagery

August 6, 2012
Author(s)
Shahram Orandi, John M. Libert, John D. Grantham, Kenneth Ko, Stephen S. Wood, Jin Chu Wu, Lindsay M. Petersen, Bruce Bandini
This paper presents the findings of a study initially conducted to measure the operational impact of JPEG 2000 lossy compression on 1000 ppi fingerprint imagery at various levels of compression, but later expanded to include lossless compression. Lossless

IREX III Supplement 1: Failure Analysis

April 18, 2012
Author(s)
George W. Quinn, Patrick J. Grother
Iris recognition has the potential to be extremely accurate, but it is highly dependent on the quality of the input data. Iris occlusion, off-axis gaze, blurred images, and iris rotation are common problems that can make recognizing individuals more

IREX III - Performance of Iris Identification Algorithms

April 3, 2012
Author(s)
Patrick J. Grother, George W. Quinn, James R. Matey, Mei L. Ngan, Wayne J. Salamon, Gregory P. Fiumara, Craig I. Watson
Iris recognition has long been held as an accurate and fast biometric. In the first public evaluation of one-to-many iris identification technologies, this third activity in the Iris Exchange (IREX) program has measured the core algorithmic efficacy and

Criteria Towards Metrics for Benchmarking Template Protection Algorithms

March 30, 2012
Author(s)
Eddy Simoens, Bian Yang, Xuebing Zhou, Filipe Beato, Christoph Busch, Elaine M. Newton, Bart Preneel
Traditional criteria used in biometric performance evaluation do not cover all the performance aspects of biometric template protection (BTP) and the lack of well-defined metrics inhibits the proper evaluation of such methods. Previous work in the

Performance of Face Recognition Algorithms on Compressed Images

December 1, 2011
Author(s)
George W. Quinn, Patrick J. Grother
This report provides a comprehensive assessment of the ability of face recognition algorithms to compare compressed standard face images. Six well performing algorithms from the Multiple Biometric Evaluation (MBE) 2010 Still Face Track are used to compare

Ocular and Iris Recognition Baseline Algorithm

November 7, 2011
Author(s)
Yooyoung Lee, Ross J. Micheals, James J. Filliben, P J. Phillips, Hassan A. Sahibzada
Due to its distinctiveness, the human eye is a popular biometricv feature used to identity a person with high accuracy. The Grand Challenge in biometrics is to have an effective algorithm for subject verification or identification under a broad range of

Data Dependency on Measurement Uncertainties in Speaker Recognition Evaluation

November 3, 2011
Author(s)
Jin Chu Wu, Alvin F. Martin, Craig S. Greenberg, Raghu N. Kacker
The National Institute of Standards and Technology (NIST) has been conducting an ongoing series of Speaker Recognition Evaluations (SRE). Speaker detection performance is measured using a detection cost function defined as a weighted sum of the
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