A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2014; you can also visit the original URL.
The file type is application/pdf
.
Filters
Cross-View Image Geolocalization
2013
2013 IEEE Conference on Computer Vision and Pattern Recognition
In this paper, we introduce a cross-view feature translation approach to greatly extend the reach of image geolocalization methods. ...
While there are many geotagged images available on photo sharing and street view sites, most are clustered around landmarks and urban areas. ...
Disclaimer: The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied ...
doi:10.1109/cvpr.2013.120
dblp:conf/cvpr/LinBH13
fatcat:dqftuzefnnew5h2ov57xht4xbi
A Faster and More Effective Cross-View Matching Method of UAV and Satellite Images for UAV Geolocalization
2021
Remote Sensing
Cross-view geolocalization matches the same target in different images from various views, such as views of unmanned aerial vehicles (UAVs) and satellites, which is a key technology for UAVs to autonomously ...
Published methods focus on extracting coarse features from parts of images, but neglect the relationship between different views, and the influence of scale and shifting. ...
Cross-view geolocalization has been a research focus in recent years due to the huge application value of geolocalization. ...
doi:10.3390/rs13193979
fatcat:rq44pd26xzhrbpkudth6d4l3vq
Cross-View Image Geo-localization
[chapter]
2016
Advances in Computer Vision and Pattern Recognition
In this paper, we introduce a cross-view feature translation approach to greatly extend the reach of image geolocalization methods. ...
While there are many geotagged images available on photo sharing and street view sites, most are clustered around landmarks and urban areas. ...
Disclaimer: The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied ...
doi:10.1007/978-3-319-25781-5_4
fatcat:wspw6crodbbkdjuhjbj446t73u
UAV Pose Estimation using Cross-view Geolocalization with Satellite Imagery
[article]
2018
arXiv
pre-print
We propose an image-based cross-view geolocalization method that estimates the global pose of a UAV with the aid of georeferenced satellite imagery. ...
We also present a framework to integrate our cross-view geolocalization output with visual odometry through a Kalman filter. ...
The other category of cross-view geolocalization implies that the method geolocates a query image using georeferenced images from a different view. ...
arXiv:1809.05979v1
fatcat:epkic6ssmfglzogi2jkkitm43q
Geolocation Assessment and Optimization for OMPS Nadir Mapper: Methodology
2022
Remote Sensing
This study presents a method for efficiently assessing OMPS-NM geolocation accuracy using spatially collocated radiance measurements from the Visible Infrared Imaging Radiometer Suite (VIIRS) Moderate ...
In addition, the assessment results can be used to optimize the OMPS-NM field view angle lookup table in the Sensor Data Record (SDR) processing software to improve its geolocation accuracy. ...
Lawrence Flynn from the NOAA/NESDIS/STAR and Glen Jaross from NASA/GFSC for their critical comments and suggestions, and Ninghai Sun and Ding Liang for their help when the first author implemented the geolocation ...
doi:10.3390/rs14133040
fatcat:qd3glyow5vgjfkdmslml73mdza
Wide-Area Image Geolocalization with Aerial Reference Imagery
[article]
2015
arXiv
pre-print
We propose to use deep convolutional neural networks to address the problem of cross-view image geolocalization, in which the geolocation of a ground-level query image is estimated by matching to georeferenced ...
We use state-of-the-art feature representations for ground-level images and introduce a cross-view training approach for learning a joint semantic feature representation for aerial images. ...
Disclaimer: The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied ...
arXiv:1510.03743v1
fatcat:twi64udpa5bxrhg4zfhhk6tv34
Wide-Area Image Geolocalization with Aerial Reference Imagery
2015
2015 IEEE International Conference on Computer Vision (ICCV)
We propose to use deep convolutional neural networks to address the problem of cross-view image geolocalization, in which the geolocation of a ground-level query image is estimated by matching to georeferenced ...
We use state-of-the-art feature representations for ground-level images and introduce a cross-view training approach for learning a joint semantic feature representation for aerial images. ...
Disclaimer: The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied ...
doi:10.1109/iccv.2015.451
dblp:conf/iccv/WorkmanSJ15
fatcat:mbxc3menl5gstn45lqw6xupgjq
GAMa: Cross-view Video Geo-localization
[article]
2022
arXiv
pre-print
The existing work in cross-view geo-localization is based on images where a ground panorama is matched to an aerial image. ...
Moreover, we propose a hierarchical approach to further improve the clip-level geolocalization. ...
Current works on cross-view geolocalization follow image based approach since the existing datasets only contain image pairs for ground and aerial view [25, 16, 9, 31, 18] . ...
arXiv:2207.02431v1
fatcat:5m2rjgnllvbljawrsqjgfoscyi
Learning deep representations for ground-to-aerial geolocalization
2015
2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
The recent availability of geo-tagged images and rich geospatial data has inspired a number of algorithms for image based geolocalization. ...
Most approaches predict the location of a query image by matching to ground-level images with known locations (e.g., street-view data). ...
Disclaimer: The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied ...
doi:10.1109/cvpr.2015.7299135
dblp:conf/cvpr/LinCBH15
fatcat:cjcqvosu45azti4n4g6zvawusu
Drone-View Building Identification by Cross-View Visual Learning and Relative Spatial Estimation
2018
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
We frame this drone-view building identification as building retrieval problem: given a building (multimodal query) with its images, geolocation and drone's current location, we aim to retrieve the most ...
Despite few annotated drone-view images to date, there are many images of other views from the Web, like ground-level, street-view and aerial images. ...
Due to the lack of annotated drone-view data, we utilize external building dataset for cross-view image matching and propose a cross-view visual learning model for drone-view image matching. ...
doi:10.1109/cvprw.2018.00197
dblp:conf/cvpr/ChenKLLH18
fatcat:53ucxjrjxnfubiiyxen76itxy4
Unmanned Aerial Vehicle (UAV) Based Point Cloud for 3D Mapping and Modelling
2020
Zenodo
image processing. ...
This paper carried out the workflow for developing a 3D model based on geo-referenced images, particularly from aerial photos obtained by a UAS; the case study also showed the latest developments of UAV ...
positions (blue crosses) and their computed positions (green crosses) in the top-view (XY plane), front-view (XZ plane), and side-view (YZ plane). ...
doi:10.5281/zenodo.4304996
fatcat:ydvtvaj3onhdljn5o7oeu5ctl4
Object-Based Visual Sentiment Concept Analysis and Application
2014
Proceedings of the ACM International Conference on Multimedia - MM '14
[Ongoing] Studying the problem of geolocalizing a street view image by matching it to bird's eye view imagery based on the learned deep feature representations. ...
Research Projects Sep. 2014now Aug. 2014now
Cross-view Geolocalization
Figure-ground segmentation with Human in the Loop Designing a stochastic approach to collect crowdsourced data for figure-ground ...
doi:10.1145/2647868.2654935
dblp:conf/mm/ChenYCCCC14
fatcat:sq66yehyzvdrtovve624qcwmpe
Planar Structure Matching under Projective Uncertainty for Geolocation
[chapter]
2014
Lecture Notes in Computer Science
Image based geolocation aims to answer the question: where was this ground photograph taken? ...
We present an approach to geolocalating a single image based on matching human delineated line segments in the ground image to automatically detected line segments in ortho images. ...
Disclaimer: The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the o cial policies or endorsements, either expressed or implied ...
doi:10.1007/978-3-319-10584-0_18
fatcat:yjiwwluk4rgi5mkhgojcfklm3q
Transformer-Guided Convolutional Neural Network for Cross-View Geolocalization
[article]
2022
arXiv
pre-print
Ground-to-aerial geolocalization refers to localizing a ground-level query image by matching it to a reference database of geo-tagged aerial imagery. ...
This is very challenging due to the huge perspective differences in visual appearances and geometric configurations between these two views. ...
With regard to cross-view geolocalization, Yang et al. ...
arXiv:2204.09967v1
fatcat:srkuqlhuznbflnbhejj37zclly
MODELS FOR PHOTOGRAMMETRIC PROCESSING OF INFORMATION FROM "RESOURCE-P" SATELLITES
2016
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Models of image geolocation used for photogrammetric processing of information from all types of imagery systems are designed. ...
<br><br> Examples of the obtained models practical application for photogrammetric processing of images from "Resource-P" satellites are shown. ...
In this case tie points on a couple of cross routes connect images from each CCD-matrix of one route with images of all CCD-matrices of the second route. ...
doi:10.5194/isprs-archives-xli-b6-169-2016
fatcat:ady5vg5tyfhp7eudbci3a657du
« Previous
Showing results 1 — 15 out of 8,610 results