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Abstract Details
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Activity Number:
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574
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Type:
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Contributed
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Date/Time:
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Wednesday, August 3, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistical Computing
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| Abstract - #301425 |
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Title:
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Biometric Face Recognition and Performance Evaluation
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Author(s):
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Geof H. Givens*+ and Ross Beveridge and Jonathon Phillips and Bruce Draper and Yui Man Lui and David Bolme
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Companies:
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Colorado State University and Colorado State University and National Institute of Standards and Technology and Colorado State University and Colorado State University and Colorado State University
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Address:
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Dept. of Statistics, CSU, Fort Collins, CO, 80523,
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Keywords:
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biometrics ;
face recognition ;
GLMM
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Abstract:
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The science of biometric face recognition is relatively unfamiliar to statisticians. We describe the major aspects of the field and outline several recognition algorithms ranging from an elementary principal components approach to quite sophisticated methods. Evaluating algorithm performance and how it relates to human, image, and environmental variables is key to advancement of the field. We summarize one performance study using a state-of-the-art commercial recognition algorithm and a generalized linear mixed model to illustrate the types of conclusions that can be made to better understand recognition performance, improve real-world applications, and develop innovative new face recognition algorithms.
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