]> 2026-04-04T16:37:24+02:00 Publications:On the role of dimensionality in face authentication 500 en <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> Symposium on image analysis, Halmstad March 7-8, 2000 http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:408419 91 Proceedings Conference Paper 87 On the role of dimensionality in face authentication 2000 2016-09-30T20:42:11Z 2457662.3626273 On the role of dimensionality in face authentication 500 0 plainlist list 1 [[:Publications:On the role of dimensionality in face authentication]] On the role of dimensionality in face authentication# QUERYa84811c71f4240b6862af1d4061a6087 500 [2,"smw-datavalue-property-restricted-annotation-use","Publisher"] On the role of dimensionality in face authentication# ERR6c155b5d70b69ddb590b4f2e73389c2a 500 [2,"smw-datavalue-property-restricted-annotation-use","Author"] On the role of dimensionality in face authentication# ERRe24f17e090c98448f3de99d03182b7b6