Least-Squares Fitting of Two 3-D Point Sets
IEEE Transactions on Pattern Analysis and Machine Intelligence
Least-Squares Estimation of Transformation Parameters Between Two Point Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Positive definite matrices and Sylvester's criterion
American Mathematical Monthly
Estimating 3-D location parameters using dual number quaternions
CVGIP: Image Understanding
Robust Parameter Estimation in Computer Vision
SIAM Review
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Anisotropic Orthogonal Procrustes Analysis
Journal of Classification
INSPECTOR: A Computer Vision System that Learns to Inspect Parts
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Pose estimation is a problem that occurs in many applications. In machine vision, the pose is often a 2D affine pose. In several applications, a restricted class of 2D affine poses with five degrees of freedom consisting of an anisotropic scaling, a rotation, and a translation must be determined from corresponding 2D points. A closed-form least-squares solution for this problem is described. The algorithm can be extended easily to robustly deal with outliers.