The University of Southampton
University of Southampton Institutional Repository

Mobile Visual Clothing Search

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.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
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.

Text
Cushen-IMV2013.pdf - Other
Download (4MB)

More information

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
ORCID for Mark S. Nixon: ORCID iD orcid.org/0000-0002-9174-5934

Catalogue record

Date deposited: 01 May 2013 13:37
Last modified: 15 Mar 2024 02:35

Export record

Contributors

Author: George Cushen
Author: Mark S. Nixon ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×