Article

Mobile museum guide based on fast SIFT recognition

Authors:

Effrosyni Kokiopoulou,

Marcin DetynieckiAuthors Info & Claims

AMR'08: Proceedings of the 6th international conference on Adaptive Multimedia Retrieval: identifying, Summarizing, and Recommending Image and Music

Pages 170 - 183

https://doi.org/10.1007/978-3-642-14758-6_14

Published: 26 June 2008 Publication History

Abstract

This article explores the feasibility of a market-ready, mobile pattern recognition system based on the latest findings in the field of object recognition and currently available hardware and network technology. More precisely, an innovative, mobile museum guide system is presented, which enables camera phones to recognize paintings in art galleries.

After careful examination, the algorithms Scale-Invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF) were found most promising for this goal. Consequently, both have been integrated in a fully implemented prototype system and their performance has been thoroughly evaluated under realistic conditions.

In order to speed up the matching process for finding the corresponding sample in the feature database, an approximation to Nearest Neighbor Search was investigated. The k-means based clustering approach was found to significantly improve the computational time.

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Cited By

Otero BRodriguez EVentura J(2017)SURF-based mammalian species identification systemMultimedia Tools and Applications10.1007/s11042-016-3602-076:7(10133-10147)Online publication date: 1-Apr-2017
https://dl.acm.org/doi/10.1007/s11042-016-3602-0
Min WJiang SWang SXu RCao YHerranz LHe Z(2017)A survey on context-aware mobile visual recognitionMultimedia Systems10.1007/s00530-016-0523-823:6(647-665)Online publication date: 1-Nov-2017
https://dl.acm.org/doi/10.1007/s00530-016-0523-8
Becattini FFerracani ALanducci LPezzatini DUricchio TDel Bimbo A(2016)Imaging Novecento. A Mobile App for Automatic Recognition of Artworks and Transfer of Artistic StylesDigital Heritage. Progress in Cultural Heritage: Documentation, Preservation, and Protection10.1007/978-3-319-48496-9_62(781-791)Online publication date: 31-Oct-2016
https://dl.acm.org/doi/10.1007/978-3-319-48496-9_62
Show More Cited By

Mobile museum guide based on fast SIFT recognition
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems

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Information & Contributors

Information

Published In

cover image Guide Proceedings

AMR'08: Proceedings of the 6th international conference on Adaptive Multimedia Retrieval: identifying, Summarizing, and Recommending Image and Music

June 2008

183 pages

ISBN:3642147577

Editors:
Marcin Detyniecki
Université Pierre et Marie Curie, Paris, France
,
Ulrich Leiner
Fraunhofer Institute for Telecommunications, Berlin, Germany
,
Andreas Nürnberger
Institute for Knowledge and Language Engineering, Faculty of Computer Science, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany

Sponsors

LDIDP: Laboratoire d'Informatique de Paris 6
Fraunhofer Institute for Telecommunications HHI, Berlin: Fraunhofer Institute for Telecommunications HHI, Berlin
Otto-von-Guericke University, Magdeburg, Germany: Otto-von-Guericke University, Magdeburg, Germany
University Pierre and Marie Curie

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 26 June 2008

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Cited By

Otero BRodriguez EVentura J(2017)SURF-based mammalian species identification systemMultimedia Tools and Applications10.1007/s11042-016-3602-076:7(10133-10147)Online publication date: 1-Apr-2017
https://dl.acm.org/doi/10.1007/s11042-016-3602-0
Min WJiang SWang SXu RCao YHerranz LHe Z(2017)A survey on context-aware mobile visual recognitionMultimedia Systems10.1007/s00530-016-0523-823:6(647-665)Online publication date: 1-Nov-2017
https://dl.acm.org/doi/10.1007/s00530-016-0523-8
Becattini FFerracani ALanducci LPezzatini DUricchio TDel Bimbo A(2016)Imaging Novecento. A Mobile App for Automatic Recognition of Artworks and Transfer of Artistic StylesDigital Heritage. Progress in Cultural Heritage: Documentation, Preservation, and Protection10.1007/978-3-319-48496-9_62(781-791)Online publication date: 31-Oct-2016
https://dl.acm.org/doi/10.1007/978-3-319-48496-9_62
Li DChuah MOoi WFeng WLiu F(2015)EMODProceedings of the 6th ACM Multimedia Systems Conference10.1145/2713168.2713172(25-36)Online publication date: 18-Mar-2015
https://dl.acm.org/doi/10.1145/2713168.2713172
Weede OMuchinenyika SMuyingi HWinschiers-Theophilus HD'Andrea VIversen O(2014)Virtual welcome guide for interactive museumsProceedings of the 13th Participatory Design Conference: Short Papers, Industry Cases, Workshop Descriptions, Doctoral Consortium papers, and Keynote abstracts - Volume 210.1145/2662155.2662222(167-169)Online publication date: 6-Oct-2014
https://dl.acm.org/doi/10.1145/2662155.2662222
Wein LJones MPalanque PSchmidt AGrossman T(2014)Visual recognition in museum guide appsProceedings of the SIGCHI Conference on Human Factors in Computing Systems10.1145/2556288.2557270(635-638)Online publication date: 26-Apr-2014
https://dl.acm.org/doi/10.1145/2556288.2557270
Urzaiz GHervás RVillarreal VBravo J(2012)Communication platform to enable collaborative tourism applicationsProceedings of the 6th international conference on Ubiquitous Computing and Ambient Intelligence10.1007/978-3-642-35377-2_51(367-370)Online publication date: 3-Dec-2012
https://dl.acm.org/doi/10.1007/978-3-642-35377-2_51
Jang YWoo W(2011)Stroke-based semi-automatic region of interest detection algorithm for in-situ painting recognitionProceedings of the 2011 international conference on Virtual and mixed reality: systems and applications - Volume Part II10.5555/2028716.2028737(167-176)Online publication date: 9-Jul-2011
https://dl.acm.org/doi/10.5555/2028716.2028737

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