A Localization Method for UAV Aerial Images Based on Semantic Topological Feature Matching
In order to address the problem of Unmanned Aerial Vehicles (UAVs) being difficult to locate in environments without Global Navigation Satellite System (GNSS) signals or with weak signals, this paper proposes a localization method for UAV aerial images based on semantic topological feature matching....
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/17/10/1671 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850126436240719872 |
|---|---|
| author | Jing He Qian Wu |
| author_facet | Jing He Qian Wu |
| author_sort | Jing He |
| collection | DOAJ |
| description | In order to address the problem of Unmanned Aerial Vehicles (UAVs) being difficult to locate in environments without Global Navigation Satellite System (GNSS) signals or with weak signals, this paper proposes a localization method for UAV aerial images based on semantic topological feature matching. Unlike traditional scene matching methods that rely on image-to-image matching technology, this approach uses semantic segmentation and the extraction of image topology feature vectors to represent images as patterns containing semantic visual references and the relative topological positions between these visual references. The feature vector satisfies scale and rotation invariance requirements, employs a similarity measurement based on Euclidean distance for matching and positioning between the target image and the benchmark map database, and validates the proposed method through simulation experiments. This method reduces the impact of changes in scale and direction on the image matching accuracy, improves the accuracy and robustness of matching, and significantly reduces the storage requirements for the benchmark map database. |
| format | Article |
| id | doaj-art-efb01ab32c89442b9514ec4f08205f0e |
| institution | OA Journals |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-efb01ab32c89442b9514ec4f08205f0e2025-08-20T02:33:55ZengMDPI AGRemote Sensing2072-42922025-05-011710167110.3390/rs17101671A Localization Method for UAV Aerial Images Based on Semantic Topological Feature MatchingJing He0Qian Wu1Information and Navigation School, Air Force Engineering University, Xi’an 710051, ChinaInformation and Navigation School, Air Force Engineering University, Xi’an 710051, ChinaIn order to address the problem of Unmanned Aerial Vehicles (UAVs) being difficult to locate in environments without Global Navigation Satellite System (GNSS) signals or with weak signals, this paper proposes a localization method for UAV aerial images based on semantic topological feature matching. Unlike traditional scene matching methods that rely on image-to-image matching technology, this approach uses semantic segmentation and the extraction of image topology feature vectors to represent images as patterns containing semantic visual references and the relative topological positions between these visual references. The feature vector satisfies scale and rotation invariance requirements, employs a similarity measurement based on Euclidean distance for matching and positioning between the target image and the benchmark map database, and validates the proposed method through simulation experiments. This method reduces the impact of changes in scale and direction on the image matching accuracy, improves the accuracy and robustness of matching, and significantly reduces the storage requirements for the benchmark map database.https://www.mdpi.com/2072-4292/17/10/1671UAVnavigation and positioningsemantic segmentationfeature matchingcomputer vision |
| spellingShingle | Jing He Qian Wu A Localization Method for UAV Aerial Images Based on Semantic Topological Feature Matching Remote Sensing UAV navigation and positioning semantic segmentation feature matching computer vision |
| title | A Localization Method for UAV Aerial Images Based on Semantic Topological Feature Matching |
| title_full | A Localization Method for UAV Aerial Images Based on Semantic Topological Feature Matching |
| title_fullStr | A Localization Method for UAV Aerial Images Based on Semantic Topological Feature Matching |
| title_full_unstemmed | A Localization Method for UAV Aerial Images Based on Semantic Topological Feature Matching |
| title_short | A Localization Method for UAV Aerial Images Based on Semantic Topological Feature Matching |
| title_sort | localization method for uav aerial images based on semantic topological feature matching |
| topic | UAV navigation and positioning semantic segmentation feature matching computer vision |
| url | https://www.mdpi.com/2072-4292/17/10/1671 |
| work_keys_str_mv | AT jinghe alocalizationmethodforuavaerialimagesbasedonsemantictopologicalfeaturematching AT qianwu alocalizationmethodforuavaerialimagesbasedonsemantictopologicalfeaturematching AT jinghe localizationmethodforuavaerialimagesbasedonsemantictopologicalfeaturematching AT qianwu localizationmethodforuavaerialimagesbasedonsemantictopologicalfeaturematching |