Identifying the Geographic Location of an Image with a Multimodal Probability Density Function
Identifying the Geographic Location of an Image with a Multimodal Probability Density Function
There is a wide array of online photographic content that is not geotagged. Algorithms for efficient and accurate geographical estimation of an image are needed to geolocate these photos. This paper presents a general model for using both textual metadata and visual features of photos to automatically place them on a world map.
Davies, Jamie
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Hare, Jonathon
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Samangooei, Sina
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Preston, John
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Jain, Neha
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Dupplaw, David
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Lewis, Paul H.
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Davies, Jamie
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Hare, Jonathon
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Samangooei, Sina
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Preston, John
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Jain, Neha
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Dupplaw, David
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Lewis, Paul H.
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Davies, Jamie, Hare, Jonathon, Samangooei, Sina, Preston, John, Jain, Neha, Dupplaw, David and Lewis, Paul H.
(2013)
Identifying the Geographic Location of an Image with a Multimodal Probability Density Function.
MediaEval 2013 / Placing: Geo-coordinate Prediction for Social Multimedia, Barcelona, Spain.
(In Press)
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Conference or Workshop Item
(Paper)
Abstract
There is a wide array of online photographic content that is not geotagged. Algorithms for efficient and accurate geographical estimation of an image are needed to geolocate these photos. This paper presents a general model for using both textual metadata and visual features of photos to automatically place them on a world map.
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Accepted/In Press date: 18 October 2013
Venue - Dates:
MediaEval 2013 / Placing: Geo-coordinate Prediction for Social Multimedia, Barcelona, Spain, 2013-10-18
Organisations:
Web & Internet Science
Identifiers
Local EPrints ID: 358836
URI: http://eprints.soton.ac.uk/id/eprint/358836
PURE UUID: e3500685-ca39-447e-b7a1-933df21bdc44
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Date deposited: 11 Oct 2013 16:49
Last modified: 15 Mar 2024 03:25
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Contributors
Author:
Jamie Davies
Author:
Jonathon Hare
Author:
Sina Samangooei
Author:
John Preston
Author:
Neha Jain
Author:
David Dupplaw
Author:
Paul H. Lewis
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