Two-dimensional heteroscedastic linear discriminant analysis for age-group classification

Kazuya Ueki, Teruhide Hayashida, Tetsunori Kobayashi

研究成果: Conference contribution

8 被引用数 (Scopus)

抄録

This paper presents a novel LDA algorithm named 2DHLDA (2-Dimensional Heteroscedastic Linear Discriminant Analysis). The proposed algorithms are applied on age-group classification using facial images under various lighting conditions. 2DHLDA significantly overcomes the singularity problem, so-called 'Small Sample Size' problem (S3 problem), and the original feature space is split into useful dimensions and nuisance dimensions to reduce the influence of different lighting conditions. A two-phased dimensional reduction step, namely 2DHLDA+LDA, is used in our experiment. Our experimental results show that the new 2DHLDA-based approach improves classification accuracy more than the conventional 1D and 2D-based approaches.

本文言語English
ホスト出版物のタイトルProceedings - 18th International Conference on Pattern Recognition, ICPR 2006
ページ585-588
ページ数4
DOI
出版ステータスPublished - 2006 12 1
イベント18th International Conference on Pattern Recognition, ICPR 2006 - Hong Kong, China
継続期間: 2006 8 202006 8 24

出版物シリーズ

名前Proceedings - International Conference on Pattern Recognition
2
ISSN(印刷版)1051-4651

Other

Other18th International Conference on Pattern Recognition, ICPR 2006
CountryChina
CityHong Kong
Period06/8/2006/8/24

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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