تقرير
Wide-Area Geolocalization with a Limited Field of View Camera in Challenging Urban Environments
| العنوان: | Wide-Area Geolocalization with a Limited Field of View Camera in Challenging Urban Environments |
|---|---|
| المؤلفون: | Downes, Lena M., Steiner, Ted J., Russell, Rebecca L., How, Jonathan P. |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Robotics |
| الوصف: | Cross-view geolocalization, a supplement or replacement for GPS, localizes an agent within a search area by matching ground-view images to overhead images. Significant progress has been made assuming a panoramic ground camera. Panoramic cameras' high complexity and cost make non-panoramic cameras more widely applicable, but also more challenging since they yield less scene overlap between ground and overhead images. This paper presents Restricted FOV Wide-Area Geolocalization (ReWAG), a cross-view geolocalization approach that combines a neural network and particle filter to globally localize a mobile agent with only odometry and a non-panoramic camera. ReWAG creates pose-aware embeddings and provides a strategy to incorporate particle pose into the Siamese network, improving localization accuracy by a factor of 100 compared to a vision transformer baseline. This extended work also presents ReWAG*, which improves upon ReWAG's generalization ability in previously unseen environments. ReWAG* repeatedly converges accurately on a dataset of images we have collected in Boston with a 72 degree field of view (FOV) camera, a location and FOV that ReWAG* was not trained on. Comment: 10 pages, 16 figures. Extension of ICRA 2023 paper arXiv:2209.11854 |
| نوع الوثيقة: | Working Paper |
| الوصول الحر: | http://arxiv.org/abs/2308.07432Test |
| رقم الانضمام: | edsarx.2308.07432 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |