Presenting and visualizing image results for professional image searchers: A field evaluation

Creative professionals such as journalists and copywriters are an important group of users who need to search for images as part of their work task. We describe the design and evaluation of a ‘high density’ image search interface targeted at this user group. We use a field evaluation together with a qualitative approach with creative professionals to gather feedback on the high density in-terface design. Our results show that creative professional viewed the interface favourably be-cause they were able to get a quick overview of research results. We make suggestions for the ap-propriateness of high density interfaces for different work contexts, and further work in terms of layouts of images in high density interfaces.

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Publication date: July 2017

Publication date (Print): July 2017

Pages: 1-5

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[ ¹ ]Ambisense Ltd

[ ² ]Centre for HCI Design, School of Mathematics, Computer Science and Engineering, University of London

Article

DOI: 10.14236/ewic/HCI2017.6

SO-VID: 73e0d1d0-7c53-46a2-a2fc-2a4b070d0049

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This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Conference name: Proceedings of the 31st International BCS Human Computer Interaction Conference (HCI 2017)

Conference acronym: HCI

Conference number: 31

Conference location: Sunderland, UK

Conference date: 3 - 6 July 2017

Conference sponsor: Electronic Workshops in Computing (eWiC)

Conference theme: digital make-believe, with delegates considering our expansive

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1477-9358 BCS Learning & Development

Self URI (article page): https://www.scienceopen.com/hosted-document?doi=10.14236/ewic/HCI2017.6

Self URI (journal page): https://ewic.bcs.org/

REFERENCES

P. BolettieriA. EsuliF. FalchiC. LuccheseR. PeregoT. PiccioliF. Rabitti 2009 CoPhIR: a Test Collection for Content-Based Image Retrieval CoRR abs/0905.4627
E.K. ChungJ.W. Yoon 2011 Image needs in the context of image use: An exploratory study J. Info. Sci 37 163 177
I. J. CoxM. L. MillerT. P. MinkaT. V. PapathomasP. N. Yianilos 2000 The Bayesian Image Retrieval System, PicHunter: Theory, Implementation, and Psychophysical Experiments IEEE Transactions on Image Processing. 9 20 37
R. DattaD. JoshiJ. LiJ.Z. Wang 2008 Image Retrieval: Ideas, Influences, and Trends of the New Age ACM Comp. Sur. 40 5:1 60
J.P. EakinsM. Graham 1999 Content-based image retrieval. JISC Technology applications program report: 39 https://tinyurl.com/hxkhbxm 9th February 2017
A. GökerR. ButterworthA. MacFarlaneT AhmedS. Stumpf 2016 Expeditions through image jungles: a study of the commercial use of image libraries. J. Doc 71 5 23
A. GökerR. ButterworthA. MacFarlaneT AhmedS. Stumpf 2017 Presenting and visualizing results on an image retrieval user interface. Proceedings of British HCI (in this volume)
M. Hearst 2009 Search User Interfaces. Chapter 10: Information visualization for search interfaces Cambridge University Press
W. PlantG. Schaefer 2011 Visualisation and browsing of Image Databases Multimedia Analysis, Processing and Communications, Studies in Computational Intelligence 346 W. Lin,D TaoJ KacprzykE IzquierdoH Wang Springer-Verlag 3 57
K. RoddenW. BasalajD. SinclairK. Wood 2001 Does organisation by similarity assist image browsing? Proc. CHI 2001 190 197 ACM Press New York
K. Rodden 2002 Evaluating similarity-based visualisations as interfaces for image browsing University of Cambridge, Computer Laboratory Technical Report No 543. UCAM-CL-TR-543
S. RobertsonS. WalkerS. JonesM. Hancock-BeaulieuM. Gatford 1994 Okapi at TREC-3 Proc. TREC-3 109 126 NIST Gaithersburg
S.J. Rose 1999 The Sunflower visual metaphor, A new paradigm for dimensional compression. In: IEEE Symposium on Information Visualisation 128 131 IEEE Press Hoboken, N.J
A. L. StraussJ. M. Corbin 1998 Basics of Qualitative Research: Techniques and Procedures for developing Grounded Theory Sage publications
R.S. TorresC.G. SilvaC.B. MedeirosH.V. Rocha 2003 Visual Structures for Image Browsing, In: Proc. CIKM 2004 49 55 ACM Press New York
H Vogel 1979 A better way to construct the sunflower head. Math. Biosci 44 179 189
Xapian Project https://xapian.org/ 9th May 2017
T. Yoshizawa 2004 User interface techniques for browsing and searching image databases. Doctoral dissertation University of Texas at Dallas USA

Comments

Comment on this article

[1] P. BolettieriA. EsuliF. FalchiC. LuccheseR. PeregoT. PiccioliF. Rabitti 2009 CoPhIR: a Test Collection for Content-Based Image Retrieval CoRR abs/0905.4627

[2] E.K. ChungJ.W. Yoon 2011 Image needs in the context of image use: An exploratory study J. Info. Sci 37 163 177

[3] I. J. CoxM. L. MillerT. P. MinkaT. V. PapathomasP. N. Yianilos 2000 The Bayesian Image Retrieval System, PicHunter: Theory, Implementation, and Psychophysical Experiments IEEE Transactions on Image Processing. 9 20 37

[4] R. DattaD. JoshiJ. LiJ.Z. Wang 2008 Image Retrieval: Ideas, Influences, and Trends of the New Age ACM Comp. Sur. 40 5:1 60

[5] J.P. EakinsM. Graham 1999 Content-based image retrieval. JISC Technology applications program report: 39 https://tinyurl.com/hxkhbxm 9th February 2017

[6] A. GökerR. ButterworthA. MacFarlaneT AhmedS. Stumpf 2016 Expeditions through image jungles: a study of the commercial use of image libraries. J. Doc 71 5 23

[7] A. GökerR. ButterworthA. MacFarlaneT AhmedS. Stumpf 2017 Presenting and visualizing results on an image retrieval user interface. Proceedings of British HCI (in this volume)

[8] M. Hearst 2009 Search User Interfaces. Chapter 10: Information visualization for search interfaces Cambridge University Press

[9] W. PlantG. Schaefer 2011 Visualisation and browsing of Image Databases Multimedia Analysis, Processing and Communications, Studies in Computational Intelligence 346 W. Lin,D TaoJ KacprzykE IzquierdoH Wang Springer-Verlag 3 57

[10] K. RoddenW. BasalajD. SinclairK. Wood 2001 Does organisation by similarity assist image browsing? Proc. CHI 2001 190 197 ACM Press New York

[11] K. Rodden 2002 Evaluating similarity-based visualisations as interfaces for image browsing University of Cambridge, Computer Laboratory Technical Report No 543. UCAM-CL-TR-543

[12] S. RobertsonS. WalkerS. JonesM. Hancock-BeaulieuM. Gatford 1994 Okapi at TREC-3 Proc. TREC-3 109 126 NIST Gaithersburg

[13] S.J. Rose 1999 The Sunflower visual metaphor, A new paradigm for dimensional compression. In: IEEE Symposium on Information Visualisation 128 131 IEEE Press Hoboken, N.J

[14] A. L. StraussJ. M. Corbin 1998 Basics of Qualitative Research: Techniques and Procedures for developing Grounded Theory Sage publications

[15] R.S. TorresC.G. SilvaC.B. MedeirosH.V. Rocha 2003 Visual Structures for Image Browsing, In: Proc. CIKM 2004 49 55 ACM Press New York

[16] H Vogel 1979 A better way to construct the sunflower head. Math. Biosci 44 179 189

[17] Xapian Project https://xapian.org/ 9th May 2017

[18] T. Yoshizawa 2004 User interface techniques for browsing and searching image databases. Doctoral dissertation University of Texas at Dallas USA

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