典型文献
Target localization based on cross-view matching between UAV and satellite
文献摘要：
Matching remote sensing images taken by an unmanned aerial vehicle(UAV)with satel-lite remote sensing images with geolocation information.Thus,the specific geographic location of the target object captured by the UAV is determined.Its main challenge is the considerable differ-ences in the visual content of remote sensing images acquired by satellites and UAVs,such as dra-matic changes in viewpoint,unknown orientations,etc.Much of the previous work has focused on image matching of homologous data.To overcome the difficulties caused by the difference between these two data modes and maintain robustness in visual positioning,a quality-aware template matching method based on scale-adaptive deep convolutional features is proposed by deeply mining their common features.The template size feature map and the reference image feature map are first obtained.The two feature maps obtained are used to measure the similarity.Finally,a heat map representing the probability of matching is generated to determine the best match in the reference image.The method is applied to the latest UAV-based geolocation dataset(University-1652 data-set)and the real-scene campus data we collected with UAVs.The experimental results demonstrate the effectiveness and superiority of the method.
文献关键词：
中图分类号：
作者姓名：
Kan REN;Lei DING;Minjie WAN;Guohua GU;Qian CHEN
作者机构：
Jiangsu Key Laboratory of Spectral Imaging and Intelligent Sense,Nanjing University of Science and Technology,Nanjing 210094,China
文献出处：
引用格式：
[1]Kan REN;Lei DING;Minjie WAN;Guohua GU;Qian CHEN-.Target localization based on cross-view matching between UAV and satellite)[J].中国航空学报（英文版）,2022(09):333-341
A类：
geolocation
B类：
Target,localization,cross,matching,between,Matching,remote,sensing,images,taken,by,unmanned,aerial,vehicle,information,Thus,specific,geographic,target,object,captured,determined,Its,challenge,considerable,ences,visual,content,acquired,satellites,UAVs,such,dra,matic,changes,viewpoint,unknown,orientations,etc,Much,previous,work,has,focused,homologous,To,overcome,difficulties,caused,difference,these,two,modes,maintain,robustness,positioning,quality,aware,template,method,scale,adaptive,convolutional,features,proposed,deeply,mining,their,common,size,reference,first,obtained,maps,measure,similarity,Finally,heat,representing,probability,generated,best,applied,latest,dataset,University,real,scene,campus,collected,experimental,results,demonstrate,effectiveness,superiority
AB值：
0.532002
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