The representation, recognition, and locating of 3-d objects
International Journal of Robotics Research
Least-Squares Fitting of Two 3-D Point Sets
IEEE Transactions on Pattern Analysis and Machine Intelligence
A few steps toward artificial 3-D vision
Robotics science
Least-Squares Estimation of Transformation Parameters Between Two Point Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Analysis of 3-D Rotation Fitting
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Given a rigid body motion expressed by a set of 2D or 3D correspondences, the distance between feature points and angular information can be used as rigid constraints to calibrate motion parameters. In this paper, we first present a novel geometrical analysis of properties of reflected correspondence vectors. The analysis provides explicit expressions for distance between feature points and angle measurement synthesised into a single coordinate frame providing the closed form solutions to all motion parameters of interest. A novel calibration algorithm is proposed and compared with an algorithm based on the least squares method. The algorithm demonstrates the importance of the geometrical properties of reflected correspondence vectors to motion parameter estimation and that it is generally more accurate than algorithms based on the least squares method.