Posture Estimation by Using High Frequency Markers and Kernel Regressions
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- Ono Yuya
- Graduate School of Engineering Science, Osaka University
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- Iwai Yoshio
- Graduate School of Engineering Science, Osaka University
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- Ishiguro Hiroshi
- Graduate School of Engineering Science, Osaka University
Bibliographic Information
- Other Title
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- 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
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Description
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
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- IEEJ Transactions on Electronics, Information and Systems
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IEEJ Transactions on Electronics, Information and Systems 130 (9), 1513-1523, 2010
The Institute of Electrical Engineers of Japan
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Details 詳細情報について
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- CRID
- 1390282679586195840
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- NII Article ID
- 10026579741
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- NII Book ID
- AN10065950
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- ISSN
- 13488155
- 03854221
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- NDL BIB ID
- 10800309
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed