Cross-View Geo-Localization for Autonomous UAV Using Locally-Aware Transformer-Based Network

3Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Although GPS is commonly used for the autonomous flying of unmanned aerial vehicles (UAVs), researchers mainly focus on image-based localization methods due to their tremendous advantages when it comes to GPS-denied environments. In this study, we study the problem of image-based geo-localization between UAV and satellite (known as cross-view geo-localization), which is an essential step towards image-based localization. In cross-view geo-localization, extracting fine-grained features containing contextual information from images is challenging due to the large gap in visual representations between different views. Existing methods in this field often use convolutional neural networks (CNNs) as feature extractors. However, CNNs have some limitations in receptive fields, which leads to the loss of fine-grained information. Some researchers have implemented Transformer-based networks to overcome these circumstances. However, these approaches only focused on understanding the meaning of each pixel based on their attention and only partially utilized tokens that are produced from Transformer blocks. Therefore, different from these works, we proposed a Vision Transformer-based network that takes advantage of local tokens, especially the classification token. Through experiments, our proposed model has significantly outperformed existing state-of-the-art models, which gave promising capabilities for developing this method in the future.

Cite

CITATION STYLE

APA

Bui, D. V., Kubo, M., & Sato, H. (2023). Cross-View Geo-Localization for Autonomous UAV Using Locally-Aware Transformer-Based Network. IEEE Access, 11, 104200–104210. https://doi.org/10.1109/ACCESS.2023.3317950

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free