Posture Estimation by Using High Frequency Markers and Kernel Regressions

• Ono Yuya

  Graduate School of Engineering Science, Osaka University

• Iwai Yoshio

  Graduate School of Engineering Science, Osaka University

• Ishiguro Hiroshi

  Graduate School of Engineering Science, Osaka University

Bibliographic Information

Other Title

• 高周波数マーカとカーネル回帰による物体の姿勢推定
• コウシュウハスウ マーカ ト カーネル カイキ ニ ヨル ブッタイ ノ シセイ スイテイ

Abstract

Recently, research fields of augmented reality and robot navigation are actively investigated. Estimating a relative posture between an object and a camera is an important task in these fields. In this paper, we propose a novel method for posture estimation by using high frequency markers and kernel regressions. The markers are embedded in an object's texture in the high frequency domain. We observe the change of spatial frequency of object's texture to estimate a current posture of the object. We conduct experiments to show the effectiveness of our method.

Journal

• IEEJ Transactions on Electronics, Information and Systems

  IEEJ Transactions on Electronics, Information and Systems 130 (9), 1513-1523, 2010

  The Institute of Electrical Engineers of Japan

Keywords

• high frequency markers
• kernel regression
• posture estimation

Details

• CRID: 1390282679586195840
• NII Article ID: 10026579741
• NII Book ID: AN10065950
• DOI: 10.1541/ieejeiss.130.1513
• ISSN: 13488155
• ISSN: 03854221
• NDL BIB ID: 10800309
• Web Site: http://id.ndl.go.jp/bib/10800309
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I10800309
• Web Site: http://www.jstage.jst.go.jp/article/ieejeiss/130/9/130_9_1513/_pdf
• Text Lang: ja
• Data Source:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed