Dynamically visual learning for people identification with sparsely distributed cameras

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

研究成果: Conference article査読

5 被引用数 (Scopus)

抄録

We propose a dynamic visual learning method that aims to identify people by using sparsely distributed multiple surveillance cameras. In the proposed method, virtual viewpoint images are synthesized by interpolating the sparsely distributed images with a simple 3D shape model of the human head, so that virtual densely distributed multiple images can be obtained. The multiple images generate an initial eigenspace in the initial learning step. In the following additional learning step, other distributed cameras capture additional images that update the eigenspace to improve the recognition performance. The discernment capability for personal identification of the proposed method is demonstrated experimentally.

本文言語English
ページ(範囲)130-140
ページ数11
ジャーナルLecture Notes in Computer Science
3540
DOI
出版ステータスPublished - 2005
イベント14th Scandinavian Conference on Image Analysis, SCIA 2005 - Joensuu, Finland
継続期間: 2005 6月 192005 6月 22

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータサイエンス一般

フィンガープリント

「Dynamically visual learning for people identification with sparsely distributed cameras」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル