Robust registration of point sets using iteratively reweighted least squares

@article{Bergstrm2014RobustRO,
  title={Robust registration of point sets using iteratively reweighted least squares},
  author={Per Bergstr{\"o}m and Ove Edlund},
  journal={Comp. Opt. and Appl.},
  year={2014},
  volume={58},
  pages={543-561}
}
Registration of point sets is done by finding a rotation and translation that produces a best fit between a set of data points and a set of model points. We use robust M-estimation techniques to limit the influence of outliers, more specifically a modified version of the iterative closest point algorithm where we use iteratively re-weighed least squares to incorporate the robustness. We prove convergence with respect to the value of the objective function for this algorithm. A comparison is… CONTINUE READING
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