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An Attention-Based Approach to Content-Based Image Retrieval

Published: 01 July 2004 Publication History

Abstract

Mark Weiser's vision that ubiquitous computing will overcome the problem of information overload by embedding computation in the environment is on the verge of becoming a reality. Nevertheless today's technology is now capable of handling many different forms of multimedia that pervade our lives and as a result is creating a healthy demand for new content management and retrieval services. This demand is everywhere; it is coming from the mobile videophone owners, the digital camera owners, the entertainment industry, medicine, surveillance, the military, and virtually every library and museum in the world where multimedia assets are lying unknown, unseen and unused.
The volume of visual data in the world is increasing exponentially through the use of digital camcorders and cameras in the mass market. These are the modern day consumer equivalents of ubiquitous computers, and, although storage space is in plentiful supply, access and retrieval remain a severe bottle-neck both for the home user and for industry. This paper describes an approach, which makes use of a visual attention model together with a similarity measure, to automatically identify salient visual material and generate searchable metadata that associates related items in a database. Such a system for content classification and access will be of great use in current and future pervasive environments where static and mobile content retrieval of visual imagery is required.

References

[1]
1 Weiser M: 'The computer for the 21st century', Sci Amer (September 1991).
[2]
2 Brown P J and Jones G J F: 'Context-aware retrieval for pervasive computing environments', IEEE International Conference Proceedings on Pervasive Computing, Zurich, Switzerland (August 2002).
[3]
3 Lee D L and Lee W-C: 'Data management in location-dependent information services', Proc IEEE International Conference on Pervasive Computing, Zurich, Switzerland (August 2002).
[4]
4 Vendrig J: 'Filter image browsing: a study of image retrieval in large pictorial databases', Master's thesis, Dept Computer Science, University of Amsterdam, The Netherlands (February 1997).
[5]
5 Stricker M and Swain M: 'The capacity of colour histogram indexing', IEEE CVPR, Seattle, pp 704-708 (1994).
[6]
6 Del Bimbo A and Pala P: 'Visual querying by color perceptive regions', Pattern Recognition, 31, pp 1241-1253 (1998).
[7]
7 Jain A K and Vailaya A: 'Image retrieval using color and shape', Pattern Recognition, 29, No 8, pp 1233-1244 (1996).
[8]
8 Ortega M, Rui Y, Chakrabarti K, Mehrotra S and Huang T S: 'Supporting similarity queries in MARS', Proceedings of Fifth ACM International Multimedia Conference, Seattle, USA (1997).
[9]
9 Mehrotra S and Chakrabarti K: 'Similarity shape retrieval in MARS', IEEE International Conference on Multimedia and Expo, New York (2000).
[10]
10 Lu G and Phillips J: 'Using perceptually weighted histograms for colour-based image retrieval', Proceedings of 4th Int Conf on Signal Processing Proceedings, ICSP '98, (Vol 2) (1998).
[11]
11 Niblack W and Flickner M: 'Query by image and video content: the QBIC system', IEEE Computer, pp 23-32 (September 1995).
[12]
12 Bach J, Fuller C, Gupta A, Hampapur A, Horowitz B, Humphrey R, Jain R and Shu C: 'The Virage image search engine: an open framework for image management', Proceedings of the SPIE Storage and Retrieval for Image and Video Databases IV, San Jose, CA, USA, pp 76-87 (February 1996).
[13]
13 Veltkamp R C and Tanase M: 'Content-based retrieval systems: a survey', (March 2001) -- http://www.aa-lab.cs.uu.nl/cbirsurvey/ cbir-survey/
[14]
14 Beige M, Benitez A B, and Chang S F: 'MetaSeek: a content-based meta-search engine for images', Proceedings of the SPIE Conference on Storage and Retrieval for Image and Video Databases VI, San Jose, CA (January 1998) -- http:// ana.ctr.columbia.edu/metaseek/
[15]
15 Kulkami S: 'Interpretation of fuzzy logic for texture queries in CBIR', in: 'Vision, Video and Graphics', Prentice Hall and Willis (2003).
[16]
16 Carson C, Belongie S, Greenspan H and Malik J: 'Blobworld: segmentation using expectation-maximisation and its application to querying', IEEE Trans PAMI, 24, No 8, pp 1026-1038 (August 2002).
[17]
17 Wang J, Li J Z and Wiederhold G: 'SIMPLIcity: semantics-sensitive integrated matching for picture libraries', IEEE Trans PAMI, 23, No 9, pp 947-963 (September 2001).
[18]
18 Smith J R and Chang S-F: 'VisualSEEk: a fully automated content-based query system', Proc ACM Int Conf Multimedia, pp 87-98, Boston, MA (November 1996).
[19]
19 Ma W-Y and Manjunath B S: 'NeTra: a toolbox for navigating large databases', Multimedia Systems, 7, pp 184-198 (1999).
[20]
20 Smeulders A W M, Worring M, Santini S, Gupta A and Jain R: 'Content-based retrieval at the end of the early years', IEEE Trans PAMI, 22, No 12, pp 1349-1379 (December 2000).
[21]
21 Vinod V and Murase H: 'Focused color intersection with efficient searching for object extraction', International Conference on Multimedia Computing and Systems, Pattern Recognition, 30, No 10, pp 1787-1797 (1997).
[22]
22 Rui Y, Huang T S, Ortega M, and Mehrotra S: 'Relevance feedback: a power tool for interactive content-based image retrieval', IEEE Trans on Circuits and Video Technology, pp 1-13 (1998).
[23]
23 Ciocca G and Schettini R: 'A multimedia search engine with relevance feedback', Proc SPIE, 4672, San Jose (January 2002).
[24]
24 Taycher L, Cascia M La, and Sclaroff S: 'Image digestion and relevance feedback in the ImageRover WWW search engine', Proc 2nd Int Conf on Visual Information Systems, San Diego, pp 85- 94 (December 1997).
[25]
25 Cox I J, Miller M L, Minka T P, Papathomas T V and Yianilos P N: 'The Bayesian image retrieval system, PicHunter: theory, implementation, and psychophysical experiments', IEEE Trans Image Processing, 9, No 1 (January 2000).
[26]
26 Innes M and Jose J M: 'A personalised information retrieval tool', 26th Int ACM SIGIP Conf on Research and Development in Information Retrieval, Toronto (July--August 2003).
[27]
27 Stentiford F W M: 'An attention based similarity measure with application to content based information retrieval', SPIE, 5021, Storage and Retrieval for Media Databases, Santa Clara (January 2003).
[28]
28 Pauwels E J and Frederix G: 'Finding Salient Regions in images: non-parametric clustering for image segmentation and grouping', Computer Vision and Image Understanding, 75, Nos 1 and 2, pp 73-85 (August 1998).
[29]
29 Salembier P: 'Overview of the MPEG-7 standard and of future challenges for visual information analysis', EURASIP Journal on Applied Signal Processing (2002).
[30]
30 Bamidele A and Stentiford F W M: 'Image retrieval: a visual attention based approach', Postgraduate Research Conference in Electronics, Photonics, Communications and Networks, and Computing Science, Hertfordshire (April 2004).
[31]
31 Stentiford F W M: 'An estimator for visual attention through competitive novelty with application to compression', Picture Coding Symposium, Seoul (April 2001).
[32]
32 Oyekoya O K and Stentiford F W M: 'Exploring human eye behaviour using a model of visual attention', International Conference on Pattern Recognition, Cambridge (August 2004).
[33]
33 Oyekoya O K and Stentiford F W M: 'Eye tracking as a new interface for image retrieval', BT Technol J, 22, No 3, pp 161- 169 (July 2004).
[34]
34 Nothdurft H-C, Gallant J L and Van Essen D C: 'Response modulation by texture surround in primate area VI: Correlates of 'popout' under anesthesia', Visual Neuroscience, 16, pp 15-34 (1999).
[35]
35 Petkov N and Westenberg M A: 'Suppression of contour perception by band-limited noise and its relation to nonclassical receptive field inhibition', Biol Cybern, 88, pp 236-246 (2003).
[36]
36 Vleugels J and Veltkamp R C: 'Efficient image retrieval through vantage objects', Pattern Recognition, 35, pp 69-80 (2002).
[37]
37 Sarvas R, Herrarte E, Wilhelm A and Davis M, 'Metadata creation system for mobile images', 2nd International Conference on Mobile Systems, Applications and Services (MobiSys 2004), Boston (2004).

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  • (2011)Automatic image tagging based on regions of interestProceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part I10.5555/2045625.2045668(300-307)Online publication date: 24-Sep-2011
  • (2007)An attention-driven model for grouping similar images with image retrieval applicationsEURASIP Journal on Advances in Signal Processing10.1155/2007/434502007:1(116-116)Online publication date: 1-Jan-2007
  • (2006)Using visual attention to extract regions of interest in the context of image retrievalProceedings of the 44th annual ACM Southeast Conference10.1145/1185448.1185588(638-643)Online publication date: 10-Mar-2006
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cover image BT Technology Journal
BT Technology Journal  Volume 22, Issue 3
July 2004
250 pages

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Kluwer Academic Publishers

United States

Publication History

Published: 01 July 2004

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View all
  • (2011)Automatic image tagging based on regions of interestProceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part I10.5555/2045625.2045668(300-307)Online publication date: 24-Sep-2011
  • (2007)An attention-driven model for grouping similar images with image retrieval applicationsEURASIP Journal on Advances in Signal Processing10.1155/2007/434502007:1(116-116)Online publication date: 1-Jan-2007
  • (2006)Using visual attention to extract regions of interest in the context of image retrievalProceedings of the 44th annual ACM Southeast Conference10.1145/1185448.1185588(638-643)Online publication date: 10-Mar-2006
  • (2005)Robust subspace analysis for detecting visual attention regions in imagesProceedings of the 13th annual ACM international conference on Multimedia10.1145/1101149.1101306(716-724)Online publication date: 6-Nov-2005
  • (2004)Intelligent Spaces — The Vision, the Opportunities and the BarriersBT Technology Journal10.1023/B:BTTJ.0000047116.13540.e022:3(15-26)Online publication date: 1-Jul-2004

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