Image compression and retrieval for Mobile Visual Search

Cao, Y; Ritz, C; Raad, R

Image compression and retrieval for Mobile Visual Search

Cao, Y

Ritz, C Raad, R

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Publication Type:: Conference Proceeding
Citation:: 2012 International Symposium on Communications and Information Technologies, ISCIT 2012, 2012, pp. 1027 - 1032
Issue Date:: 2012-12-01

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Field	Value	Language
dc.contributor.author	Cao, Y https://orcid.org/0000-0002-7623-9830	en_US
dc.contributor.author	Ritz, C	en_US
dc.contributor.author	Raad, R	en_US
dc.date.issued	2012-12-01	en_US
dc.identifier.citation	2012 International Symposium on Communications and Information Technologies, ISCIT 2012, 2012, pp. 1027 - 1032	en_US
dc.identifier.isbn	9781467311571	en_US
dc.identifier.uri	http://hdl.handle.net/10453/119554
dc.description.abstract	Mobile Visual Search (MVS) is an emerging area of research given the explosion of smart and computationally powerful mobile devices. Typically, MVS involves the computation of local image features which are then used within a matching process. Such applications pose certain unique challenges due to computation, power and bandwidth constraints of the mobile device. This paper examines the trade-off between two general frameworks for implementing MVS: 1. sending compressed images and performing feature extraction and matching on a server; and 2. performing feature extraction on the mobile device and sending these to a server for matching. A number of local image feature algorithms are studied using various image compression schemes from the point view of matching accuracy and processing time. Results show that the matching accuracy of sending compressed images is comparable to sending compact image features when using a high quality image coder, in this case JPEG2000 and HDPhoto. © 2012 IEEE.	en_US
dc.relation.ispartof	2012 International Symposium on Communications and Information Technologies, ISCIT 2012	en_US
dc.relation.isbasedon	10.1109/ISCIT.2012.6380842	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Image compression and retrieval for Mobile Visual Search	en_US
dc.type	Conference Proceeding
utslib.for	0906 Electrical and Electronic Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access	*
pubs.publication-status	Published	en_US

Abstract:

Mobile Visual Search (MVS) is an emerging area of research given the explosion of smart and computationally powerful mobile devices. Typically, MVS involves the computation of local image features which are then used within a matching process. Such applications pose certain unique challenges due to computation, power and bandwidth constraints of the mobile device. This paper examines the trade-off between two general frameworks for implementing MVS: 1. sending compressed images and performing feature extraction and matching on a server; and 2. performing feature extraction on the mobile device and sending these to a server for matching. A number of local image feature algorithms are studied using various image compression schemes from the point view of matching accuracy and processing time. Results show that the matching accuracy of sending compressed images is comparable to sending compact image features when using a high quality image coder, in this case JPEG2000 and HDPhoto. © 2012 IEEE.

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http://hdl.handle.net/10453/119554