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Geo-distinctive Visual Element Matching for Location Estimation of Images
[article]
2016
arXiv
pre-print
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We propose an image representation and matching approach that substantially improves visual-based location estimation for images. ...
We then maximize the influence of visual elements that are geo-distinctive because they do not occur in images taken at many other locations. ...
This paper introduces a visual matching approach to image geo-location estimation that exploits geo-distinctive visual elements, referred to as distinctive visual element matching (DVEM). ...
arXiv:1601.07884v1
fatcat:ylmzbtqxqbbepjgfoxwm2n74dy
Geo-Distinctive Visual Element Matching for Location Estimation of Images
2018
IEEE transactions on multimedia
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We propose an image representation and matching approach that substantially improves visual-based location estimation for images. ...
We then maximize the influence of visual elements that are geo-distinctive because they do not occur in images taken at many other locations. ...
This paper introduces a visual matching approach to image geo-location estimation that exploits geo-distinctive visual elements, referred to as distinctive visual element matching (DVEM). ...
doi:10.1109/tmm.2017.2763323
fatcat:ogmmdytufzbpfdrdw23af3kp3y
Looking around in the neighbourhood: Location estimation of outdoor urban images
2021
IET Image Processing
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Visual geolocalisation has remained as a challenge in the research community: Given a query image, and a geo-tagged reference database, the goal is to derive a location estimate for the query image. ...
By introducing the neighbouring images, the visual information of a candidate location has been enriched. ...
Sio-Long Lo and Professor Ah Chung Tsoi for their comments on earlier versions of the manuscript. ...
doi:10.1049/ipr2.12190
fatcat:67vnrmniarbubirfvuic3mc6xi
Where to be wary: The impact of widespread photo-taking and image enhancement practices on users' geo-privacy
[article]
2016
arXiv
pre-print
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Today's geo-location estimation approaches are able to infer the location of a target image using its visual content alone. ...
These approaches exploit visual matching techniques, applied to a large collection of background images with known geo-locations. ...
The visual elements that allow GLE to geo-locate the images in the first column of Fig. 1 range from fairly obvious to barely noticeable. ...
arXiv:1603.01335v1
fatcat:6wc6lx3hlzdlhoktplucy5afoe
What makes Paris look like Paris?
2012
ACM Transactions on Graphics
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Abstract Given a large repository of geotagged imagery, we seek to automatically find visual elements, e.g. windows, balconies, and street signs, that are most distinctive for a certain geo-spatial area ...
elements at different geo-spatial scales, and geographically-informed image retrieval. ...
This work is a part of a larger effort with Dan Huttenlocher and David Crandall, on modeling geo-informative visual attributes. We thank Google for letting us publish the Street View images. ...
doi:10.1145/2185520.2335452
fatcat:vtoxulxwqrcdtjxtijbgddrdhm
What makes Paris look like Paris?
2015
Communications of the ACM
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Abstract Given a large repository of geotagged imagery, we seek to automatically find visual elements, e.g. windows, balconies, and street signs, that are most distinctive for a certain geo-spatial area ...
elements at different geo-spatial scales, and geographically-informed image retrieval. ...
This work is a part of a larger effort with Dan Huttenlocher and David Crandall, on modeling geo-informative visual attributes. We thank Google for letting us publish the Street View images. ...
doi:10.1145/2830541
fatcat:6h4ynxh72vez7iazwui5usvnay
What makes Paris look like Paris?
2012
ACM Transactions on Graphics
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Abstract Given a large repository of geotagged imagery, we seek to automatically find visual elements, e.g. windows, balconies, and street signs, that are most distinctive for a certain geo-spatial area ...
elements at different geo-spatial scales, and geographically-informed image retrieval. ...
This work is a part of a larger effort with Dan Huttenlocher and David Crandall, on modeling geo-informative visual attributes. We thank Google for letting us publish the Street View images. ...
doi:10.1145/2185520.2185597
fatcat:vo67dw6kjjdcrnw3u6acaumtfe
Visual Geo-localization of Non-photographic Depictions via 2D–3D Alignment
[chapter]
2016
Advances in Computer Vision and Pattern Recognition
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Similar to object detection, the set of visual elements, as well as the weights of individual features for each element, are learnt in a discriminative fashion. ...
We show that the learnt visual elements are reliably matched in 2D depictions of the scene despite large variations in rendering style (e.g. watercolor, sketch, historical photograph) and structural changes ...
, of IARPA, AFRL or the U.S. ...
doi:10.1007/978-3-319-25781-5_14
fatcat:6rszhn7wlrevliycdiogncravu
Topic Models for Image Localization
2013
2013 International Conference on Computer and Robot Vision
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Topic Models for Image Localization 2013 We present a new scheme for partitioning geo-tagged reference image database in an effort to speed up query image localization while maintaining acceptable localization ...
The query image is localized using the location information associated with the visually similar images in the reference database. ...
Helala-for their support and friendship. Our discussions were most enjoyable. Special thanks to my supervisor Dr. Faisal Z. Qureshi for his support, guidance and encouragement. ...
doi:10.1109/crv.2013.36
dblp:conf/crv/WangQ13
fatcat:43daigumjbddfmaciic3kqno2q
Predicting Good Features for Image Geo-Localization Using Per-Bundle VLAD
2015
2015 IEEE International Conference on Computer Vision (ICCV)
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We address the problem of recognizing a place depicted in a query image by using a large database of geo-tagged images at a city-scale. ...
Also, for both learning to predict features and retrieving geo-tagged images from the database, we propose per-bundle vector of locally aggregated descriptors (PBVLAD), where each maximally stable region ...
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, of IARPA ...
doi:10.1109/iccv.2015.139
dblp:conf/iccv/KimDF15
fatcat:f74k7gpmqvfb3k6f74ch5jg5he
Discovering Geo-Informative Attributes for Location Recognition and Exploration
2014
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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This article considers the problem of automatically discovering geo-informative attributes for location recognition and exploration. ...
The attributes are expected to be both discriminative and representative, which correspond to certain distinctive visual patterns and associate with semantic interpretations. ...
For a set of unlabeled geo-informative attributes, we first retrieve the visual neighbors from the user-tagged image database in the location. ...
doi:10.1145/2648581
fatcat:wjjt6h6yljbk5mr2wpqj6i5i2a
Ten-fold Improvement in Visual Odometry Using Landmark Matching
2007
2007 IEEE 11th International Conference on Computer Vision
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At each visited location along the route, a set of distinctive visual landmarks is automatically extracted and inserted into a landmark database dynamically. ...
Our goal is to create a visual odometry system for robots and wearable systems such that localization accuracies of centimeters can be obtained for hundreds of meters of distance traveled. ...
On the other hand, the distinctive SIFT features [13] are detected and matched to a pre-built SIFT database map to locate itself for a robot globally. ...
doi:10.1109/iccv.2007.4409062
dblp:conf/iccv/ZhuOSKS07
fatcat:dkgsv5dstzawdnuob6fuybizjy
Learned Contextual Feature Reweighting for Image Geo-Localization
2017
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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We address the problem of large scale image geolocalization where the location of an image is estimated by identifying geo-tagged reference images depicting the same place. ...
Our model is learned end-to-end for the image geo-localization task, and requires no annotation other than image geo-tags for training. ...
, of IARPA, AFRL, or the U.S. ...
doi:10.1109/cvpr.2017.346
dblp:conf/cvpr/KimDF17
fatcat:erayhg6jozgi3ipazp3ud4ibru
Scene Signatures: Localised and Point-less Features for Localisation
2014
Robotics: Science and Systems X
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We present an unsupervised system that produces broad-region detectors for distinctive visual elements, called scene signatures, which can be associated across almost all appearance changes. ...
We show, using 21 km of data collected over a period of 3 months, that our system is capable of producing metric estimates from night-to-day or summer-to-winter conditions. ...
[18] presented a method for extracting geo-distinctive image patches from a collection of images of London and Paris. ...
doi:10.15607/rss.2014.x.023
dblp:conf/rss/McManusUN14
fatcat:llrytq6m6fh33dgx5kmp5w2kr4
GIANT
2013
Proceedings of the 21st ACM international conference on Multimedia - MM '13
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This paper considers the problem of automatically discovering geo-informative attributes for location recognition and exploration. ...
Experimental results show that: (1) geo-informative attributes are discriminative and useful for location recognition; (2) the discovered semantic interpretation is meaningful and can be exploited for ...
Estimating the geographical information directly from image visual content is a challenging problem. ...
doi:10.1145/2502081.2502088
dblp:conf/mm/FangSX13
fatcat:3hxgaznlpvg7pggwg7gbpvjdge
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