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Information Technology

Biometrics

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Displaying 326 - 350 of 804

Examination of Downsampling Strategies for Converting 1000 ppi Fingerprint Imagery to 500 ppi

January 22, 2013
Author(s)
Shahram Orandi, John M. Libert, John D. Grantham, Lepley Margaret, Bruce Bandini, Kenneth Ko, Lindsay M. Petersen, Stephen S. Wood, Stephen G. Harvey
Currently the bulk of fingerprint data in operational is captured, processed and stored at 500 ppi using the WSQ compressed digital format. With the transition to 1000 ppi, some systems will unavoidably contain an overlap between 500 ppi and 1000 ppi

Video-based Face Recognition via Joint Sparse Representation

January 2, 2013
Author(s)
P J. Phillips, Vishal M. Patel, Yi-Chen Chen, Rama Chellappa
In video-based face recognition, a key challenge is in exploiting the extra information available in a video. In addition, different video sequences of the same subject may contain variations in resolution, illumination, pose, and facial expressions. These

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