| Item type |
デフォルトアイテムタイプ_（フル）(1) |
| 公開日 |
2023-03-18 |
| タイトル |
|
|
タイトル |
Linear Discriminative Image Processing Operator Analysis |
|
言語 |
en |
| 作成者 |
Tamaki, Toru
Yuan, Bingzhi
Harada, Kengo
Raytchev, Bisser
Kaneda, Kazufumi
|
| アクセス権 |
|
|
アクセス権 |
open access |
|
アクセス権URI |
http://purl.org/coar/access_right/c_abf2 |
| 権利情報 |
|
|
権利情報 |
Copyright (c) 2012 IEEE |
| 主題 |
|
|
主題Scheme |
NDC |
|
主題 |
540 |
| 内容記述 |
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|
内容記述 |
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. |
|
言語 |
en |
| 出版者 |
|
|
出版者 |
IEEE |
| 言語 |
|
|
言語 |
eng |
| 資源タイプ |
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|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_5794 |
|
資源タイプ |
conference paper |
| 出版タイプ |
|
|
出版タイプ |
AO |
|
出版タイプResource |
http://purl.org/coar/version/c_b1a7d7d4d402bcce |
| 関連情報 |
|
|
|
識別子タイプ |
URI |
|
|
関連識別子 |
http://ir.lib.hiroshima-u.ac.jp/00033094 |
| 収録物識別子 |
|
|
収録物識別子タイプ |
ISSN |
|
収録物識別子 |
1063-6919 |
| 開始ページ |
|
|
開始ページ |
2526 |
| 書誌情報 |
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR2012)
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR2012)
p. 2526-2532,
発行日 2012
|
| 旧ID |
33093 |
cvpr2012-tamaki.pdf (250.8 KB)
