Combining Absolute and Semi-Generalized Relative Poses for Visual Localization
<|reference_start|>Combining Absolute and Semi-Generalized Relative Poses for Visual Localization: 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.<|reference_end|>
@article{panek2024combining,
    title={Combining Absolute and Semi-Generalized Relative Poses for Visual
  Localization},
    author={Vojtech Panek, Torsten Sattler, Zuzana Kukelova},
    journal={arXiv preprint arXiv:2409.14269},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.14269},
    primaryClass={cs.CV}
}