research-article

Energy conservation by adaptive feature loading for mobile content-based image retrieval

Authors:

Karthik Kumar,

Yamini Nimmagadda,

Yu-Ju Hong,

Yung-Hsiang LuAuthors Info & Claims

ISLPED '08: Proceedings of the 2008 international symposium on Low Power Electronics & Design

Pages 153 - 158

https://doi.org/10.1145/1393921.1393963

Published: 11 August 2008 Publication History

Publisher Site Get Access

Abstract

We present an adaptive loading scheme to save energy for content based image retrieval (CBIR) in a mobile system. In CBIR, images are represented and compared by high-dimensional vectors called features. Loading these features into memory and comparing them consumes a significant amount of energy. Our method adaptively reduces the features to be loaded into memory for each query image. The reduction is achieved by estimating the difficulty of the query and by reusing cached features in memory for subsequent queries. We implement our method on a PDA and obtain overall energy reduction of 61.3% compared with an existing CBIR implementation.

References

[1]

I. Ahmad and M. Gabbouj. Compression and Network Effect on Content-Based Image Retrieval on Java Enabled Mobile Devices. In Finnish Signal Processing Symposium, pages 35--38, 2005.

Google Scholar

[2]

R. Datta, D. Joshi, J. Li, and J. Z. Wang. Image Retrieval: Ideas, Influences, and Trends of the New Age. ACM Computing Surveys, 40:5:1--5:60, April 2008.

Digital Library

Google Scholar

[3]

J. Forster. Reducing Time and RAM Requirements in Content-Based Image Retrieval using Retrieval Filtering. In Informatiktage, pages 143--146, 2007.

Google Scholar

[4]

J. C. French, W. N. Martin, and J. V. S. Watson. A Qualitative Examination of Content-Based Image Retrieval Behavior using Systematically Modified Test Images. In Midwest Symposium on Circuits and Systems, pages 655--658, 2002.

Crossref

Google Scholar

[5]

N. J. Gunther and G. Beretta. A Benchmark for Image Retrieval using Distributed Systems over the Internet:BIRDS-I. In SPIE - Internet Imaging II, pages 252--267, 2001.

Google Scholar

[6]

C. E. Jacobs, A. Finkelstein, and D. H. Salesin. Fast Multiresolution Image Querying. In International Conference on Computer Graphics and Interactive Techniques, pages 277--286, 1995.

Digital Library

Google Scholar

[7]

M. Jia, X. Fan, X. Xie, M. Li, and W.-Y. Ma. Photo-to-Search: Using Camera Phones to Inquire of the Surrounding World. In International Conference on Mobile Data Management, pages 46--46, 2006.

Digital Library

Google Scholar

[8]

O. Robles, J. Bosque, L. Pastor, and A. Rodriguez. Performance analysis of a cbir system on shared-memory systems and heterogeneous clusters. In Computer Architecture for Machine Perception, pages 309--314, 2005.

Digital Library

Google Scholar

[9]

S. Rudinac, G. Zajic, M. Uscumlic, M. Rudinac, and B. Reljin. Comparison of cbir systems with different number of feature vector components. Semantic Media Adaptation and Personalization, pages 199--204, 2007.

Digital Library

Google Scholar

[10]

T. Yeh, K. Tollmar, and T. Darrell. Searching the Web with Mobile Images for Location Recognition. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pages 76--81, 2004.

Digital Library

Google Scholar

Cited By

View all

Damahe LThakur N(2019)Review on Image Representation Compression and Retrieval ApproachesTechnological Innovations in Knowledge Management and Decision Support10.4018/978-1-5225-6164-4.ch009(203-231)Online publication date: 2019
https://doi.org/10.4018/978-1-5225-6164-4.ch009
Jiang YXu XTerlecky PAbdelzaher TBar-Noy AGovindan RAbdelzaher TRömer KRajkumar R(2013)MediaScopeProceedings of the 12th international conference on Information processing in sensor networks10.1145/2461381.2461416(289-300)Online publication date: 8-Apr-2013
https://dl.acm.org/doi/10.1145/2461381.2461416
Li KZhu CLv QShang LDick R(2013)Personalized multi-modality image management and search for mobile devicesPersonal and Ubiquitous Computing10.1007/s00779-013-0660-417:8(1817-1834)Online publication date: 1-Dec-2013
https://dl.acm.org/doi/10.1007/s00779-013-0660-4
Show More Cited By

Index Terms

Energy conservation by adaptive feature loading for mobile content-based image retrieval
1. General and reference
  1. Cross-computing tools and techniques
    1. Design
2. Information systems
  1. Information retrieval

Recommendations

Energy Conservation for Image Retrieval on Mobile Systems

Mobile systems such as PDAs and cell phones play an increasing role in handling visual contents such as images. Thousands of images can be stored in a mobile system with the advances in storage technology: this creates the need for better organization ...
Content-based image retrieval: a deep look at features prospectus

Currently, rapid growth of digital images on the internet is observed, accordingly, the need for content-based image retrieval systems are in high demand. Content-based image retrieval CBIR is an image search technique that does not depend on manually ...
An adaptive technique for content-based image retrieval

We discuss an adaptive approach towards Content-Based Image Retrieval. It is based on the Ostensive Model of developing information needs--a special kind of relevance feedback model that learns from implicit user feedback and adds a temporal notion to ...

Comments

Information & Contributors

Information

Published In

ISLPED '08: Proceedings of the 2008 international symposium on Low Power Electronics & Design

August 2008

396 pages

ISBN:9781605581095

DOI:10.1145/1393921

General Chairs:
Vijaykrishnan Narayanan
Penn State University
,
C. P. Ravikumar
Texas Instruments
,
Joerg Henkel
Univeristy of Karlsruhe
,
Ali Keshavarzi
Intel Corporation
,
Program Chairs:
Vojin G. Oklobdzija
University of Texas at Dallas
,
Barry Pangrle
Pangrle Consulting

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 August 2008

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

ISLPED08

Sponsor:

ISLPED08: International Symposium on Low Power Electronics and Design

August 11 - 13, 2008

Bangalore, India

Acceptance Rates

Overall Acceptance Rate 398 of 1,159 submissions, 34%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

9
Total Citations
View Citations
243
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 10 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Damahe LThakur N(2019)Review on Image Representation Compression and Retrieval ApproachesTechnological Innovations in Knowledge Management and Decision Support10.4018/978-1-5225-6164-4.ch009(203-231)Online publication date: 2019
https://doi.org/10.4018/978-1-5225-6164-4.ch009
Jiang YXu XTerlecky PAbdelzaher TBar-Noy AGovindan RAbdelzaher TRömer KRajkumar R(2013)MediaScopeProceedings of the 12th international conference on Information processing in sensor networks10.1145/2461381.2461416(289-300)Online publication date: 8-Apr-2013
https://dl.acm.org/doi/10.1145/2461381.2461416
Li KZhu CLv QShang LDick R(2013)Personalized multi-modality image management and search for mobile devicesPersonal and Ubiquitous Computing10.1007/s00779-013-0660-417:8(1817-1834)Online publication date: 1-Dec-2013
https://dl.acm.org/doi/10.1007/s00779-013-0660-4
Kumar KNimmagadda YLu Y(2012)Energy Conservation for Image Retrieval on Mobile SystemsACM Transactions on Embedded Computing Systems10.1145/2345770.234577911:3(1-22)Online publication date: 1-Sep-2012
https://dl.acm.org/doi/10.1145/2345770.2345779
Cascia MMorana MVella F(2010)Automatic image representation and clustering on mobile devicesJournal of Mobile Multimedia10.5555/2016968.20169746:2(158-169)Online publication date: 1-Jun-2010
https://dl.acm.org/doi/10.5555/2016968.2016974
La Cascia MMorana MSorce S(2010)Mobile Interface for Content-Based Image ManagementProceedings of the 2010 International Conference on Complex, Intelligent and Software Intensive Systems10.1109/CISIS.2010.172(718-723)Online publication date: 15-Feb-2010
https://dl.acm.org/doi/10.1109/CISIS.2010.172
Fay DShang LGrunwald DHenkel JParameswaran S(2009)A platform for developing adaptable multicore applicationsProceedings of the 2009 international conference on Compilers, architecture, and synthesis for embedded systems10.1145/1629395.1629418(157-166)Online publication date: 11-Oct-2009
https://dl.acm.org/doi/10.1145/1629395.1629418
Kumar KNimmagadda YLu YHenkel JKeshavarzi AChang NGhani T(2009)Ranking servers based on energy savings for computation offloadingProceedings of the 2009 ACM/IEEE international symposium on Low power electronics and design10.1145/1594233.1594296(267-272)Online publication date: 19-Aug-2009
https://dl.acm.org/doi/10.1145/1594233.1594296
Zhu CLi KLv QShang LDick RZielinski KWolisz AFlinn JLaMarca A(2009)iScopeProceedings of the 7th international conference on Mobile systems, applications, and services10.1145/1555816.1555845(277-290)Online publication date: 22-Jun-2009
https://dl.acm.org/doi/10.1145/1555816.1555845

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Abstract

References

Cited By

Index Terms

Recommendations

Energy Conservation for Image Retrieval on Mobile Systems

Content-based image retrieval: a deep look at features prospectus

An adaptive technique for content-based image retrieval

Comments

Information

Published In

Sponsors

Publisher

Publication History

Permissions

Check for updates

Author Tags

Qualifiers

Conference

Acceptance Rates

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

Login options

Full Access

View options

PDF

eReader

Share

Share this Publication link

Share on social media

Affiliations