“Dynamically Visual Learning for Person Identification with Sparsely Distributed Multiple Cameras”

Hidenori Tanaka, Hideo Saito, Itaru Kitahara, Hiroshi Murase, Kiyoshi Kogure, Norihiro Hagita

研究成果: Article査読

抄録

This paper proposes a dynamical visual learning method, which aims to identify person using multiple surveillance cameras sparsely distributed in space. In the proposed method, densely distributed multiple images are captured by interpolating the object' s appearance in the sparsely distributed multiple images with a simple 3D face model, and generate two initial eigenspaces (an eigenspace for pose estimation and that for identification). In case another image is captured, the object's pose and name are estimated using the eigenspaces. The image is projected onto the 3D face model as texture information to improve the object's appearance, and the eigenspaces are regenerated. The discernment capability for person identification of the proposed method is shown by experimental results.

本文言語English
ページ(範囲)623-633
ページ数11
ジャーナルJournal of the Institute of Image Electronics Engineers of Japan
38
5
DOI
出版ステータスPublished - 2009 1

ASJC Scopus subject areas

  • コンピュータ サイエンス(その他)
  • 電子工学および電気工学

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