Robust estimation of three-dimensional motion parameters from a sequence of imag
IEEE Transactions on Pattern Analysis and Machine Intelligence
Closed form solutions to image flow equations for planar surfaces in motion
Computer Vision, Graphics, and Image Processing
Structure and motion from optical flow under perspective projection
Computer Vision, Graphics, and Image Processing
Robust regression and outlier detection
Robust regression and outlier detection
Optical Flow with an Intensity-Weighted Smoothing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ambiguities of a Motion Field
Optimal Visual Motion Estimation: A Note
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unbiased Estimation and Statistical Analysis of 3-D Rigid Motion from Two Views
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimal Motion and Structure Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Concerns the estimation of the motion parameters of a rigid body from noisy point matches made on perspective views. A minimization problem which permits relatively robust parameter estimation and helps overcome poor zoom estimation when the field-of-view is small is formulated. It is assumed that the motion has a small rotary component, interframe differences are small, and the errors in the system are due to independently distributed errors in the components of the displacement vectors. A fast procedure for minimization is exposited, in which the parameter set is partitioned and conditional generalized least-squares formulas identified. Recursive application of these provides the search space for the minimization problem. Comparative results are presented using simulated data and displacement vectors obtained from an intensity-based matching algorithm.