Mobile Visual Clothing Search
Mobile Visual Clothing Search
We present a mobile visual clothing search system whereby a smart phone user can either choose a social networking photo or take a new photo of a person wearing clothing of interest and search for similar clothing in a retail database. From the query image, the person is detected, clothing is segmented, and clothing features are extracted and quantized. The information is sent from the phone client to a server, where the feature vector of the query image is used to retrieve similar clothing products from online databases. The phone's GPS location is used to re-rank results by retail store location. State of the art work focusses primarily on the recognition of a diverse range of clothing offline and pays little attention to practical applications. Evaluated on a challenging dataset, the system is relatively fast and achieves promising results.
Cushen, George
52f73d41-3ae0-4c11-a50a-86e782c03745
Nixon, Mark S.
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Cushen, George
52f73d41-3ae0-4c11-a50a-86e782c03745
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Cushen, George and Nixon, Mark S.
(2013)
Mobile Visual Clothing Search.
IEEE International Workshop on Intelligent Mobile Vision.
(In Press)
Record type:
Conference or Workshop Item
(Paper)
Abstract
We present a mobile visual clothing search system whereby a smart phone user can either choose a social networking photo or take a new photo of a person wearing clothing of interest and search for similar clothing in a retail database. From the query image, the person is detected, clothing is segmented, and clothing features are extracted and quantized. The information is sent from the phone client to a server, where the feature vector of the query image is used to retrieve similar clothing products from online databases. The phone's GPS location is used to re-rank results by retail store location. State of the art work focusses primarily on the recognition of a diverse range of clothing offline and pays little attention to practical applications. Evaluated on a challenging dataset, the system is relatively fast and achieves promising results.
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Cushen-IMV2013.pdf
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Accepted/In Press date: April 2013
Venue - Dates:
IEEE International Workshop on Intelligent Mobile Vision, 2013-04-01
Organisations:
Vision, Learning and Control
Identifiers
Local EPrints ID: 352095
URI: http://eprints.soton.ac.uk/id/eprint/352095
PURE UUID: 03aae393-d43d-48ae-a45b-893ed713c8f5
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Date deposited: 01 May 2013 13:37
Last modified: 15 Mar 2024 02:35
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Contributors
Author:
George Cushen
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