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J. Weng, N. Ahuja, T.S. Huang, "Optimal Motion and Structure Estimation," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 15, no. 9, pp. 864884, September, 1993.  
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@article{ 10.1109/34.232074, author = {J. Weng and N. Ahuja and T.S. Huang}, title = {Optimal Motion and Structure Estimation}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {15}, number = {9}, issn = {01628828}, year = {1993}, pages = {864884}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.232074}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
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TY  JOUR JO  IEEE Transactions on Pattern Analysis and Machine Intelligence TI  Optimal Motion and Structure Estimation IS  9 SN  01628828 SP864 EP884 EPD  864884 A1  J. Weng, A1  N. Ahuja, A1  T.S. Huang, PY  1993 KW  optimal motion estimation; nonlinear function minimization; structure estimation; epipolar information; noise distribution; minimisation; motion estimation VL  15 JA  IEEE Transactions on Pattern Analysis and Machine Intelligence ER   
The causes of existing linear algorithms exhibiting various high sensitivities to noise are analyzed. It is shown that even a small pixellevel perturbation may override the epipolar information that is essential for the linear algorithms to distinguish different motions. This analysis indicates the need for optimal estimation in the presence of noise. Methods are introduced for optimal motion and structure estimation under two situations of noise distribution: known and unknown. Computationally, the optimal estimation amounts to minimizing a nonlinear function. For the correct convergence of this nonlinear minimization, a twostep approach is used. The first step is using a linear algorithm to give a preliminary estimate for the parameters. The second step is minimizing the optimal objective function starting from that preliminary estimate as an initial guess. A remarkable accuracy improvement has been achieved by this twostep approach over using the linear algorithm alone.
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