Motion and structure from image sequences
Motion and Structure from Image Sequences is invaluable reading for researchers, graduate students, and practicing engineers dealing with computer vision. It presents a balanced treatment of the theoretical and practical issues, including very recent results - some of which are published here for the first time. The topics covered in detail are: - image matching and optical flow computation - structure from stereo - structure from motion - motion estimation - integration of multiple views - motion modeling and prediction Aspects such as uniqueness of the solution, degeneracy conditions, error analysis, stability, optimality, and robustness are also investigated. These details together with the fact that the algorithms are accessible without necessarily studying the rest of the material, make this book particularly attractive to practitioners.
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3-D points 3-D position Chapter closed-form solution components Computer Vision coordinate system cornerness covariance matrix Cramer-Rao bound defined denote depth determined discussed displacement field displacement vectors edge eigenvalue eigenvector epipolar constraint equations error estimation estimated error feature points IEEE IEEE Computer Soc IEEE Trans IEKF image coordinates image errors image frames image plane image point image sequences image vectors initial guess intensity interframe motion Kalman filtering least-squares solution linear algorithm Machine Intell matrix-weighted method minimizing motion and structure motion estimation motion parameters nonlinear Number of point objective function observations optical flow orthogonal orthogonal matrix Pattern Anal perturbation pixel point correspondences presence of noise problem Proc projection quaternion relative errors rigid motion robust rotation angle rotation axis rotation matrix scale factor scene sequential shown in Fig simulations solve surface T. S. Huang Theorem tion translation vector two-view motion unit vector variance Washington D.C. zero
Total Least Squares and Errors-in-Variables Modeling: Analysis, Algorithms ...
S. van Huffel,P. Lemmerling
No preview available - 2002
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