| Abstract
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<p>A study of the dimensionality of … <p>A study of the dimensionality of the Face Authentication problem using Principal Component Analysis (PCA) and a novel dimensionality reduction algorithm that we call Support Vector Features (SVF) is presented. Starting from a Gabor feature space, we show that PCA and SVF identify distinct subspaces with comparable authentication and generalisation performance. Experiments using KNN classifiers and Support Vector Machines (SVMs) indicate that the number of PCs or SVF required for the authentication performance to saturate heavily depends on the choice of the classifier. SVMs appear to be vulnerable to excessive PCA-based compression.</p>excessive PCA-based compression.</p>
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| Author
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F. Smeraldi +
, Josef Bigun +
, W. Gerstner +
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| Conference
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Symposium on image analysis, Halmstad March 7-8, 2000
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| Diva
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http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:408419
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| EndPage
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91 +
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| HostPublication
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Proceedings +
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| PublicationType
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Conference Paper +
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| Publisher
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Högskolan i Halmstad +
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| StartPage
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87 +
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| Title
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On the role of dimensionality in face authentication +
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| Year
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2000 +
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| Has queryThis property is a special property in this wiki.
|
Publications:On the role of dimensionality in face authentication +
, Publications:On the role of dimensionality in face authentication +
, Publications:On the role of dimensionality in face authentication +
, Publications:On the role of dimensionality in face authentication +
, Publications:On the role of dimensionality in face authentication +
, Publications:On the role of dimensionality in face authentication +
, Publications:On the role of dimensionality in face authentication +
, Publications:On the role of dimensionality in face authentication +
, Publications:On the role of dimensionality in face authentication +
, Publications:On the role of dimensionality in face authentication +
|
| Categories |
Publication +
|
| Modification dateThis property is a special property in this wiki.
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30 September 2016 20:42:11 +
|
