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arXiv · 2409.14269

Combining Absolute and Semi-Generalized Relative Poses for Visual Localization

Vojtech Panek·Torsten Sattler·Zuzana Kukelova
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Abstract

Visual localization is the problem of estimating the camera pose of a given query image within a known scene. Most state-of-the-art localization approaches follow the structure-based paradigm and use 2D-3D matches between pixels in a query image and 3D points in the scene for pose estimation. These approaches assume an accurate 3D model of the scene, which might not always be available, especially if only a few images are available to compute the scene representation. In contrast, structure-less methods rely on 2D-2D matches and do not require any 3D scene model. However, they are also less accurate than structure-based methods. Although one prior work proposed to combine structure-based and structure-less pose estimation strategies, its practical relevance has not been shown. We analyze combining structure-based and structure-less strategies while exploring how to select between poses obtained from 2D-2D and 2D-3D matches, respectively. We show that combining both strategies improves localization performance in multiple practically relevant scenarios.

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Vojtech Panek, Torsten Sattler, Zuzana Kukelova. 2024-09-21. Combining Absolute and Semi-Generalized Relative Poses for Visual Localization. https://arxiv.org/abs/2409.14269

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