Do not Omit Local Minimizer: a Complete Solution for Pose Estimation from 3D Correspondences

@article{Zhou2019DoNO,
  title={Do not Omit Local Minimizer: a Complete Solution for Pose Estimation from 3D Correspondences},
  author={Lipu Zhou and Shengze Wang and Jiamin Ye and Michael Kaess},
  journal={CoRR},
  year={2019},
  volume={abs/1904.01759}
}
Estimating pose from given 3D correspondences, including point-to-point, point-to-line and point-to-plane correspondences, is a fundamental task in computer vision with many applications. We present a complete solution for this task, including a solution for the minimal problem and the least-squares problem of this task. Previous works mainly focused on finding the global minimizer to address the leastsquares problem. However, existing works that show the ability to achieve global minimizer are… CONTINUE READING
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