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Nonlinear Mean Shift for Robust Pose Estimation

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3 Author(s)

We propose a new robust estimator for camera pose estimation based on a recently developed nonlinear mean shift algorithm. This allows us to treat pose estimation as a clustering problem in the presence of outliers. We compare our method to RANSAC, which is the standard robust estimator for computer vision problems. We also show that under fairly general assumptions our method is provably better than RANSAC. Synthetic and real examples to support our claims are provided

Published in:

Applications of Computer Vision, 2007. WACV '07. IEEE Workshop on

Date of Conference:

Feb. 2007