このエントリーをはてなブックマークに追加
ID 33093
本文ファイル
著者
Yuan, Bingzhi
Harada, Kengo
Raytchev, Bisser
NDC
電気工学
抄録(英)
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.
掲載誌名
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR2012)
開始ページ
2526
終了ページ
2532
出版年月日
2012
出版者
IEEE
ISSN
1063-6919
言語
英語
NII資源タイプ
会議発表論文
広大資料タイプ
会議発表論文
DCMIタイプ
text
フォーマット
application/pdf
著者版フラグ
author
権利情報
Copyright (c) 2012 IEEE
関連情報URL
部局名
工学研究科