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Paper detail

Robust Large-Scale Localization in 3D Point Clouds Revisited

We tackle the problem of getting a full 6-DOF pose estimation of a query image inside a given point cloud. This technical report re-evaluates the algorithms proposed by Y. Li et al. "Worldwide Pose Estimation using 3D Point Cloud". Our code computes poses from 3 or 4 points, with both known and unknown focal length. The results can easily be displayed and analyzed with Meshlab. We found both advantages and shortcomings of the methods proposed. Furthermore, additional priors and parameters for point selection, RANSAC and pose quality estimate (inlier test) are proposed and applied.

preprint2015arXivOpen access
Fabian TschoppMarco Zorzi
Computer Vision
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Fabian TschoppMarco Zorzi

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