Abstract
The motion recovery for a class of movements in the space is considered in this note by using the stereo perspective observation of at least three points. The motion equation that is considered can cover a wide class of practical movements in the space. The asymptotic estimation of the motion parameters, which are all time-dependent variables, is developed based on the second method of Lyapunov. Furthermore, the proposed algorithm can be modified to deal with occlusion phenomenon. To illustrate the performance of the proposed algorithm, it is compared with the extended Kalman filter (EKF) by computer simulations.
| Original language | English |
|---|---|
| Article number | 5779707 |
| Pages (from-to) | 2660-2665 |
| Number of pages | 6 |
| Journal | IEEE Transactions on Automatic Control |
| Volume | 56 |
| Issue number | 11 |
| DOIs | |
| Publication status | Published - 2011 Nov |
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Keywords
- Extended Kalman filter
- motion recovery
- nonlinear system
- observer
- perspective observation
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Control and Systems Engineering
- Computer Science Applications
Cite this
Motion recovery by using stereo perspective observation. / Chen, Xinkai; Kano, Hiroyuki.
In: IEEE Transactions on Automatic Control, Vol. 56, No. 11, 5779707, 11.2011, p. 2660-2665.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Motion recovery by using stereo perspective observation
AU - Chen, Xinkai
AU - Kano, Hiroyuki
PY - 2011/11
Y1 - 2011/11
N2 - The motion recovery for a class of movements in the space is considered in this note by using the stereo perspective observation of at least three points. The motion equation that is considered can cover a wide class of practical movements in the space. The asymptotic estimation of the motion parameters, which are all time-dependent variables, is developed based on the second method of Lyapunov. Furthermore, the proposed algorithm can be modified to deal with occlusion phenomenon. To illustrate the performance of the proposed algorithm, it is compared with the extended Kalman filter (EKF) by computer simulations.
AB - The motion recovery for a class of movements in the space is considered in this note by using the stereo perspective observation of at least three points. The motion equation that is considered can cover a wide class of practical movements in the space. The asymptotic estimation of the motion parameters, which are all time-dependent variables, is developed based on the second method of Lyapunov. Furthermore, the proposed algorithm can be modified to deal with occlusion phenomenon. To illustrate the performance of the proposed algorithm, it is compared with the extended Kalman filter (EKF) by computer simulations.
KW - Extended Kalman filter
KW - motion recovery
KW - nonlinear system
KW - observer
KW - perspective observation
UR - http://www.scopus.com/inward/record.url?scp=80455150114&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=80455150114&partnerID=8YFLogxK
U2 - 10.1109/TAC.2011.2158169
DO - 10.1109/TAC.2011.2158169
M3 - Article
AN - SCOPUS:80455150114
VL - 56
SP - 2660
EP - 2665
JO - IEEE Transactions on Automatic Control
JF - IEEE Transactions on Automatic Control
SN - 0018-9286
IS - 11
M1 - 5779707
ER -