Robust Visual Localization through Covisibility-Guided 2D-3D Matching with Fused Descriptors - Lidholm,Johanna (Master’s Theses in Mathematical Sciences, 2025)
In this thesis project we present a 2D-3D matching method leveraging fused local and global descriptors for robust camera pose estimation. The query image is localized by incorporating a covisibility search method to identify multiple candidate parts of the scene where the query camera is likely to be located. The localization begins with a search that looks through database images, collect associated 3D points and expands the 3D points through a covisibility expansion. The keypoints in the query image are then matched to the expanded 3D points to compute a 6-DoF pose estimation. We achieve similar results in terms of robustness as state-of-the-art methods on some established benchmarks. We also present ablation studies of our choices of hyperparameters as well as suggestions of improvements of our method.
Keywords: Visual localization; direct matching; image retrieval