Manifold learning based on multi-feature for road-sign recognition

Qieshi Zhang*, Sei Ichiro Kamata

*この研究の対応する著者

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

In this paper, a multi-feature selection and application based manifold learning metric method is proposed for Road-Sign Recognition (RSR). Firstly, the manifold metric between manifold from subspace is discussed in detail. After that, the multi-feature analyzing, selection, classification and application are introduced for rough recognition and create the manifold. Then the proposed method is used to evaluate the distance between the manifolds. Finally, the RSR results suggest that the proposed method is robust than other methods.

本文言語English
ホスト出版物のタイトルSICE 2011 - SICE Annual Conference 2011, Final Program and Abstracts
出版社Society of Instrument and Control Engineers (SICE)
ページ1143-1146
ページ数4
ISBN(印刷版)9784907764395
出版ステータスPublished - 2011 1月 1
イベント50th Annual Conference on Society of Instrument and Control Engineers, SICE 2011 - Tokyo, Japan
継続期間: 2011 9月 132011 9月 18

出版物シリーズ

名前Proceedings of the SICE Annual Conference

Other

Other50th Annual Conference on Society of Instrument and Control Engineers, SICE 2011
国/地域Japan
CityTokyo
Period11/9/1311/9/18

ASJC Scopus subject areas

  • 制御およびシステム工学
  • コンピュータ サイエンスの応用
  • 電子工学および電気工学

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