TY - GEN
T1 - Motion recovery for movements under perspective observation
AU - Chen, Xinkai
AU - Kano, Hiroyuki
PY - 2003/12/1
Y1 - 2003/12/1
N2 - The recovery of motion for a class of movements in the space by using the perspective observation of one point, where the motion parameters are all time-varying, is considered in this paper. The motion equation can cover a wide class of practical movements in the space. The estimation of the position and the motion parameter are simultaneously developed in the proposed algorithm. The formulated problem can be converted into the observation of a dynamical system with nonlinearities. The proposed observer is based on the second method of Lyapunov. First, the parameters relating to the rotation of the motion are identified, where only one camera is needed. Then the position of the moving object is identified, where the stereo vision is necessary. Finally, the parameters relating to the straight movement are identified. The assumptions about the perspective system are reasonable, and the convergence conditions are intuitive and have apparently physical interpretations. Further, the occurrence of occlusion is considered in the recovery algorithm.
AB - The recovery of motion for a class of movements in the space by using the perspective observation of one point, where the motion parameters are all time-varying, is considered in this paper. The motion equation can cover a wide class of practical movements in the space. The estimation of the position and the motion parameter are simultaneously developed in the proposed algorithm. The formulated problem can be converted into the observation of a dynamical system with nonlinearities. The proposed observer is based on the second method of Lyapunov. First, the parameters relating to the rotation of the motion are identified, where only one camera is needed. Then the position of the moving object is identified, where the stereo vision is necessary. Finally, the parameters relating to the straight movement are identified. The assumptions about the perspective system are reasonable, and the convergence conditions are intuitive and have apparently physical interpretations. Further, the occurrence of occlusion is considered in the recovery algorithm.
KW - Machine vision
KW - Motion recovery
KW - Nonlinear system
KW - Occlusion
KW - Perspective observation
UR - http://www.scopus.com/inward/record.url?scp=1542643444&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=1542643444&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:1542643444
SN - 0889863555
T3 - Proceedings of the IASTED International Conference on Intelligent Systems and Control
SP - 418
EP - 423
BT - Proceedings of the IASTED International Conference on Intelligent Systems and Control
A2 - Hamza, M.H.
A2 - Hamza, M.H.
T2 - Proceedings of the IASTED International Conference on Intelligent Systems and Control
Y2 - 25 June 2003 through 27 June 2003
ER -