Isimloc: Visual Global Localization For Previously Unseen Environments With Simulated Images
2022 · Peng Yin, Ivan Cisneros, Ji Zhang, et al.
Abstract
The visual camera is an attractive device in beyond visual line of sight (B-VLOS) drone operation, since they are low in size, weight, power, and cost, and can provide redundant modality to GPS failures. However, state-of-the-art visual localization algorithms are unable to match visual data that have a significantly different appearance due to illuminations or viewpoints. This paper presents iSimLoc, a condition/viewpoint consistent hierarchical global re-localization approach. The place features of iSimLoc can be utilized to search target images under changing appearances and viewpoints. Additionally, our hierarchical global re-localization module refines in a coarse-to-fine manner, allowing iSimLoc to perform a fast and accurate estimation. We evaluate our method on one dataset with appearance variations and one dataset that focuses on demonstrating large-scale matching over a long flight in complicated environments. On our two datasets, iSimLoc achieves 88.7% and 83.8% successful r
Authors
(none)
Tags
Stats
Related papers
- Exploring The Best Way For UAV Visual Localization Under Low-altitude Multi-view Observation Condition: A Benchmark (2025)4.25
- VICI: Vlm-instructed Cross-view Image-localisation (2025)2.51
- Localization Of Autonomous Vehicles: Proof Of Concept For A Computer Vision Approach (2021)0.00
- Probabilistic Visual Place Recognition For Hierarchical Localization (2021)11.08
- Domain-invariant Similarity Activation Map Contrastive Learning For Retrieval-based Long-term Visual Localization (2020)13.72
- Improved Visual Localization Via Graph Smoothing (2019)0.00
- Multiview Image-based Localization (2025)0.00
- BEV-CV: Birds-eye-view Transform For Cross-view Geo-localisation (2023)5.84