抄録
We consider a problem of recovering motion of an object moving in space under perspective observation. It is assumed that the motion equation is described by a linear system with unknown constant motion parameters and that a single feature point on the object is perspectively observed by two cameras. Then we analyze the identifiability of motion parameters from the stereo image data observed over an interval of time. The identifiability problem is solved by employing theories on linear dynamical systems, and the condition, established as a necessary and sufficient condition, turns out to be the controllability of a modified linear system. Such an analysis is essential when we develop and use any algorithms involving motion parameter identification. Finally, we include numerical results by employing the extended Kalman filter.
| 元の言語 | English |
|---|---|
| ホスト出版物のタイトル | Proceedings of the IASTED International Conference on Modelling, Identification and Control |
| 編集者 | M.H. Hamza |
| ページ | 103-108 |
| ページ数 | 6 |
| 巻 | 23 |
| 出版物ステータス | Published - 2004 |
| 外部発表 | Yes |
| イベント | Proceedings of the 23rd IASTED International Conference on Modelling, Identification, and Control - Grindelwald, Switzerland 継続期間: 2004 2 23 → 2004 2 25 |
Other
| Other | Proceedings of the 23rd IASTED International Conference on Modelling, Identification, and Control |
|---|---|
| 国 | Switzerland |
| 市 | Grindelwald |
| 期間 | 04/2/23 → 04/2/25 |
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ASJC Scopus subject areas
- Engineering(all)
これを引用
Motion recovery of moving objects under perspective stereo vision. / Kano, Hiroyuki; Fujioka, Hiroyuki; Chen, Xinkai; Sato, Takehito.
Proceedings of the IASTED International Conference on Modelling, Identification and Control. 版 / M.H. Hamza. 巻 23 2004. p. 103-108 412-224.研究成果: Conference contribution
}
TY - GEN
T1 - Motion recovery of moving objects under perspective stereo vision
AU - Kano, Hiroyuki
AU - Fujioka, Hiroyuki
AU - Chen, Xinkai
AU - Sato, Takehito
PY - 2004
Y1 - 2004
N2 - We consider a problem of recovering motion of an object moving in space under perspective observation. It is assumed that the motion equation is described by a linear system with unknown constant motion parameters and that a single feature point on the object is perspectively observed by two cameras. Then we analyze the identifiability of motion parameters from the stereo image data observed over an interval of time. The identifiability problem is solved by employing theories on linear dynamical systems, and the condition, established as a necessary and sufficient condition, turns out to be the controllability of a modified linear system. Such an analysis is essential when we develop and use any algorithms involving motion parameter identification. Finally, we include numerical results by employing the extended Kalman filter.
AB - We consider a problem of recovering motion of an object moving in space under perspective observation. It is assumed that the motion equation is described by a linear system with unknown constant motion parameters and that a single feature point on the object is perspectively observed by two cameras. Then we analyze the identifiability of motion parameters from the stereo image data observed over an interval of time. The identifiability problem is solved by employing theories on linear dynamical systems, and the condition, established as a necessary and sufficient condition, turns out to be the controllability of a modified linear system. Such an analysis is essential when we develop and use any algorithms involving motion parameter identification. Finally, we include numerical results by employing the extended Kalman filter.
KW - Controllability
KW - Machine vision
KW - Motion recovery
KW - Perspective stereo vision
UR - http://www.scopus.com/inward/record.url?scp=11844255695&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=11844255695&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:11844255695
VL - 23
SP - 103
EP - 108
BT - Proceedings of the IASTED International Conference on Modelling, Identification and Control
A2 - Hamza, M.H.
ER -