A Novel Semantic Geo-Localization Approach with Satellite Images for GPS-Free Navigation of UAV

Yu Cheng Cheng, Yung Jhe Yan, Peng Jie Chen, Cheng Chuan Hsu, Chun Yan Lo, Cong Yuan Chou, Chi Han Lin, Mang Ou-Yang*

*此作品的通信作者

研究成果: Conference contribution同行評審

摘要

Image geo-localization estimates an image's global position by comparing it with a large-scale image database containing known positions. This localization technology can serve as an alternative positioning method for unmanned aerial vehicles (UAV) in situations where a global position system is unavailable. Feature-based image-matching methods typically involve descriptors constructed from pixel-level key points in the images. The number of descriptors in one image can be substantial. Filtering and comparing these large quantities of descriptors for image matching would be quite time-consuming. Due to the large scale of satellite images, matching them with aerial images using this method can be challenging to achieve in real-time. Thus, this paper proposes a semantic matching-based approach for real-time image geo-localization. The types, quantities, and geometric information of objects in satellite images are extracted and used as sematic-level descriptors. The sematic-level descriptors of an aerial image captured by UAV are extracted by an object recognition model. The quantity of semantic-level descriptors is orders of magnitude less than pixel-level descriptors. The location of the aerial image can be rapidly determined by matching the semantic-level descriptors between the aerial image and satellite images. In the experiments, the speeds of matching an aerial image with satellite images using the semantic matching and a feature-based matching method were 0.194 seconds per image and 125.68 seconds per image, respectively. Using semantic matching methods is 648 times faster than using feature matching methods. The results demonstrate that the proposed semantic matching methods have the potential for real-time image geo-localization.

原文English
主出版物標題Artificial Intelligence and Image and Signal Processing for Remote Sensing XXX
編輯Lorenzo Bruzzone, Francesca Bovolo
發行者SPIE
ISBN(電子)9781510681002
DOIs
出版狀態Published - 2024
事件Artificial Intelligence and Image and Signal Processing for Remote Sensing XXX 2024 - Edinburgh, 英國
持續時間: 16 9月 202418 9月 2024

出版系列

名字Proceedings of SPIE - The International Society for Optical Engineering
13196
ISSN(列印)0277-786X
ISSN(電子)1996-756X

Conference

ConferenceArtificial Intelligence and Image and Signal Processing for Remote Sensing XXX 2024
國家/地區英國
城市Edinburgh
期間16/09/2418/09/24

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