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ID 33093
file
creator
Yuan, Bingzhi
Harada, Kengo
Raytchev, Bisser
NDC
Electrical engineering
abstract
In this paper, we propose a method to select a discriminative set of image processing operations for Linear Discriminant Analysis (LDA) as an application of the use of generating matrices representing image processing operators acting on images. First we show that generating matrices can be used for formulating LDA with increasing training samples, then analyze them as image processing operators acting on 2D continuous functions for compressing many large generating matrices by using PCA and Hermite decomposition. Then we propose Linear Discriminative Image Processing Operator Analysis, an iterative method for estimating LDA feature space along with a discriminative set of generating matrices. In experiments, we demonstrate that discriminative generating matrices outperform a nondiscriminative set on the ORL and FERET datasets.
journal title
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR2012)
start page
2526
end page
2532
date of issued
2012
publisher
IEEE
issn
1063-6919
language
eng
nii type
Conference Paper
HU type
Conference Papers
DCMI type
text
format
application/pdf
text version
author
rights
Copyright (c) 2012 IEEE
relation url
department
Graduate School of Engineering