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G.S.J. Young, R. Chellappa, "3D Motion Estimation Using a Sequence of Noisy Stereo Images: Models, Estimation, and Uniqueness Results," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 12, no. 8, pp. 735759, August, 1990.  
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@article{ 10.1109/34.57666, author = {G.S.J. Young and R. Chellappa}, title = {3D Motion Estimation Using a Sequence of Noisy Stereo Images: Models, Estimation, and Uniqueness Results}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {12}, number = {8}, issn = {01628828}, year = {1990}, pages = {735759}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.57666}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE Transactions on Pattern Analysis and Machine Intelligence TI  3D Motion Estimation Using a Sequence of Noisy Stereo Images: Models, Estimation, and Uniqueness Results IS  8 SN  01628828 SP735 EP759 EPD  735759 A1  G.S.J. Young, A1  R. Chellappa, PY  1990 KW  computer vision; nondegenerate motion; 3D motion estimation; noisy stereo images; uniqueness; kinematic modelbased approach; constant acceleration translational motion; constant precession rotational motion; bilinear statespace model; 3D feature points; nonlinear filters; CramerRao performance bounds; parameter estimates; degenerate motions; computer vision; kinematics; parameter estimation VL  12 JA  IEEE Transactions on Pattern Analysis and Machine Intelligence ER   
A kinematic modelbased approach for the estimation of 3D motion parameters from a sequence of noisy stereo images is discussed. The approach is based on representing the constant acceleration translational motion and constant precession rotational motion in the form of a bilinear statespace model using standard rectilinear states for translation and quaternions for rotation. Closedform solutions of the state transition equations are obtained to propagate the quaternions. The measurements are noisy perturbations of 3D feature points represented in an inertial coordinate system. It is assumed that the 3D feature points are extracted from the stereo images and matched over the frames. Owing to the nonlinearity in the state model, nonlinear filters are designed for the estimation of motion parameters. Simulation results are included. The CramerRao performance bounds for motion parameter estimates are computed. A constructive proof for the uniqueness of motion parameters is given. It is shown that with uniform sampling in time, three noncollinear feature points in five consecutive binocular image pairs contain all the spatial and temporal information. Both nondegenerate and degenerate motions are analyzed. A deterministic algorithm to recover motion parameters from a stereo image sequence is summarized from the constructive proof.
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