Registration of Uncertain Geometric Features: Estimating the Pose and its Accuracy (1998)
| Venue: | In Proc of the First Image Registration Workshop |
| Citations: | 2 - 2 self |
BibTeX
@INPROCEEDINGS{Pennec98registrationof,
author = {Xavier Pennec},
title = {Registration of Uncertain Geometric Features: Estimating the Pose and its Accuracy},
booktitle = {In Proc of the First Image Registration Workshop},
year = {1998}
}
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Abstract
We provide in this article a generic framework for the pose estimation from geometric features. We propose more particularly three algorithms: a gradient descent on the Riemannian least square distance and on the Mahalanobis distance, and an Extended Kalman Filter. For all these methods, we provide a way to compute the uncertainty of the resulting transformation. The analysis and comparison of the algorithms show how to combine them in a powerful and high level statistical registration algorithm. An application in medical image analysis demonstrate the usefulness of the method.
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