GDS:drone image-guided cross-view image geographic positioning

doi:10.13474/j.cnki.11-2246.2025.0711

Abstract

Abstract: Cross-view image geographic positioning refers to the method of matching the ground-view image with unknown geographic coordinates with the reference satellite image with high precision spatial coordinate information,so as to determine the geographical coordinates of the ground-view image.Due to the large difference in viewing angle between the unpositioned ground viewing angle image and the reference Satellite image,it is difficult to retrieve and match.In this paper,a UAV image-guided cross-viewing angle geographic positioning method ground-drone-satellite(GDS) is proposed,which uses the tilting photographic image of low-altitude UAV as a transition.Firstly,the unpositioned ground view image is matched with the UAV image,and then the retrieved UAV image is matched with the satellite image with accurate geographic coordinates,so as to determine the geographical position of the ground view image.In this paper,the ConvNeXt model based on convolutional neural network and Vision Transformer is used to extract image features,and InfoNCE loss is used as the training target for comparative learning,which improves the accuracy of image query.Meanwhile,random sampling strategy is adopted to disrupt and randomly remove a small part of training samples.The generalization ability of the model is improved.Experimental results on University-1652,a universal cross-view data set,show that the proposed method is superior to the method for retrieving satellite images directly from ground-view images in terms of Recall and average accuracy AP.In this paper,the accuracy of querying UAV view images from the ground perspective is 11.63%Recall@1,and the accuracy of querying satellite view images from the UAV view is 91.49%Recall@1.The two-stage retrieval method is comprehensively used to query satellite view images from the ground view images,and the accuracy reaches 10.64%Recall@1.Compared with 5.23%Recall@1 in the direct retrieval of satellite images from the ground perspective,this is a great improvement,which verifies the effectiveness and advancement of the proposed method.

Key words: image geo-localization, cross-view, drone images, satellite images, ConvNeXt, InfoNCE loss

CLC Number:

P237

XI Zexin, LI Jiayi, XIE Hao, GAN Wenjian, ZHOU Yang. GDS:drone image-guided cross-view image geographic positioning[J]. Bulletin of Surveying and Mapping, 2025, 0(7): 66-72.

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