- P-ISSN1013-0799
- E-ISSN2586-2073
- KCI
색에 의한 질의: 시각정보 검색을 위한 질의 패러다임의 유용성 측정
Query by Colour : Investigating the Efficacy of Query Paradigms for Visual Information Retrieval
Abstract
The ability of the searcher to express their information problem to an information retrieval system is fundamental to the retrieval process. Query by visual example is the principal query paradigm for expressing queries in a content-based image retrieval environment yet there is little empirical evidence to support its efficacy in facilitating query formulation. The aim of this research was to investigate the usability of the query by colour method in supporting a range of information problems in order to contribute to the gap in knowledge regarding the relationship between searchers’ information problems and the query methods required to support efficient and effective visual query formulation. The results strongly suggest that the query method does not support visual query formulation and that there is a significant mismatch between the searchers information problems and the expressive power of the retrieval paradigm.
- keywords
- colour retrieval, content-based image retrieval, image retrieval, query by visual example, query by colour, visual information retrieval, usability, 컬러 검색, 내용기반 이미지 검색, 이미지 검색, 컬러에 의한 질의, 시각 정보검색, 유용성
참고문헌
Armitage, L. H. (1997). Analysis of user need in image archives. Journal of Information Science, 23(4), 287-299.
Batley, S. (1988). Visual information retrieval: browsing strategies in pictorial databases (373-381). Online Information '88: Proceedings of the 12th International Online Information Meeting, 6th-8th December 1988, London, England.
Berlin, B. (1991). Basic Color Terms: Their Universality and Evolution:University of California Press.
Bird, C. (1999). Content-based retrieval for European image libraries (-). The Challenge of Image Retrieval: CIR99, The 2nd UK Conference on Image Retrieval, Forte Posthouse Hotel, Newcastle upon Tyne, United Kingdom, 25th-26th February 1999.
Brady, M. (2004). Grid computing for digital mammography (723-730). AHM’'2003: Proceedings of UK e-Science All Hands Meeting 2003, Nottingham, UK, 2-4th September 2003.
Castelli, V. (2002). Image Databases: Search and Retrieval of Digital Imagery:John Wiley & Sons.
Chan, H. C. (2006). Human factors in color-based image retrieval: an emprical study on size estimate accuracies. Journal of Visual Communication & Image Representation, 15(2), 113-131.
Chin, J. (1988). Development of an instrument measuring user satisfaction of the human-computer interface (213-218). CHI '88: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Washington, D.C. USA, 15-19 May 1988. ACM Press.
Conniss, L. R. (2001). Information seeking behaviour in image retrieval: VISOR I. Institute for Image Data Research.
Datta, R. (2008). Image retrieval: ideas, influences, and trends of the new age. ACM Computing Surveys, 40(2), -.
Del Bimbo, A. (1999). Visual Information Retrieval:Morgan Kaufmann.
Dunlop, M. (1991). Multimedia information retrieval.
Eidenberger, H. (2003). VizIR: a framework for visual information retrieval. Journal of Visual Languages and Computing, 14(5), 443-469.
Enser, P. G. B. (1995). Progress in documentation pictorial information retrieval. Journal of Documentation, 51(2), 126-170.
Enser, P. G. B. (1992). Analysis of visual information retrieval queries. British Library.
Feng, D. (2003). Multimedia information retrieval and management: technological fundamentals and applications. Springer-Verlag.
Fidel, R. (1997). The image retrieval task: implications for the design and evaluation of image databases. The New Review of Hypermedia and Multimedia, 3, 181-199.
Frøkjær, E. (2000). Measuring usability: are effectiveness, efficiency, and satisfaction really correlated? (345-352). CHI’'00: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, The Hague, The Netherlands, 01- 06, April, 2000. ACM Press.
Flickner, M. (1995). Query by image and video content: the QBIC system. IEEE Computer, 28(9), 23-32.
Gudivada, V. N. (1995). Contentbased image retrieval systems. IEEE Computer, 28(9), 20-.
Hanjalic, A. (2006). Multimedia content analysis, management and retrieval: trends and challenges (-). Electronic Imaging 2006, Multimedia Content Analysis, Management and Retrieval 2006, IS&T/SPIE International Symposium, SPIE Vol. 6073. San Jose Marriott and San Jose Convention Centre,.
Hirata, K. (1992). Query by visual example (56-71). EDBT’'92: Advances in Database Technology: Proceedings of the 3rd International Conference on Extending Database Technology, Vienna, Austria, 23rd-27th March 1992. Springer-Verlag.
Hix, D. (1993). Developing User Interfaces: Ensuring Usability Through Product and Process:John Wiley.
Hua, X-S. (2010). How to realize content analysis in web-scale multimedia search (-). CIVR 2010: ACM International Conference on Image and Video Retrieval, Xi'an, China 5-7 July, 2010.
Huang, J. (1997). Image indexing using color correlogram (762-768). CVPR '97: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, San Juan, Puerto Rico, 17-19 June, 1997, IEEE Computer Society.
Idris, F. (1997). Review of image and video indexing techniques. Journal of Visual Communication and Image Representation, 8(2), 146-166.
Jaimes, A. (2002). Concepts and techniques for indexing visual concep. In: Image Databases: Search and Retrieval of Digital Imagery:John Wiley & Sons Inc.
Johnson, F. C. (2001). DEVISE: a framework for the evaluation of internet search engines. The Council for Museums Archives and Libraries.
Jörgensen, C. (1995). Image attributes: an investigation.
Jose, J. M. (1998). Spatial querying for image retrieval: a user-oriented evaluation (232-240). SIGIR: Proceedings of the 21st Annual International Conference On Research And Development in Information Retrieval, University of Melbourne, 24-28 August 1998. ACM Press.
Kato, T. (1991). Intelligent visual interaction with image database systems: toward the multimedia personal interfa. Journal of Information Processing, 14(2), 134-143.
Kato, T. (1989). Multimedia interaction with image database Systems (271-278). Advanced Database System Symposium ’'89, Kyoto, Japan.
Korfhage, R. R. (1997). Information Storage and Retrieval:John Wiley & Sons.
Lai, T-S. (2000). CHROMA: a photographic image retrieval system.
Lai, T-S. (2000). A user-centred evaluation of visual search methods for CBIR (-). CIR2000: The Challenge for Image Retrieval, Third UK Conference on Image Retrieval, Old Ship Hotel, Brighton, UK, 4th-5th May 2000.
Lancaster, F. W. (1993). Information Retrieval Today:Information Resources Press.
Lew, M. S. (2001). Visual information retrieval: paradigms, applications, and research issu. in Principles of Visual Information Retrieval:Springer- Verlag.
Lu, H. (1994). Efficient image retrieval by color contents (95-108). Springer.
McDonald, S. (2001). Evaluating a content-based image retrieval system (232-240). SIGIR’'01: Proceedings of the 24th Annual International ACM Special Interest Group on Information Retrieval Conference on Research and Development in Information Retrieval, New Orleans, Louisiana, US. ACM Press.
Markkula, M. (1998). Searching for photos: journalist practices in pictorial IR (-). CIR98: The Challenge of Image Retrieval Workshop, University of Northumbria at Newcastle, Newcastle upon Tyne, United Kingdom, 5th February 1998.
Mintzer, F. (2001). Populating the hermitage museums new web site. Communications of the ACM, 44(8), 52-60.
Müller, W. (2000). MRML: an extensible communication protocol for interoperability and benchmarking of multimedia information retrieval systems. in Visual Information and Information Systems.
Niblack, C. W. (1993). The QBIC project: querying images by content using color, texture and shape (173-187). Storage and Retrieval for Image and Video Databases, Proceedings of the Society of the Photo- Optical Instrumentation Engineers Vol. 1908, San Jose, CA, USA, 31 January-5 February 1993.
Norman, D. A. (1981). Categorisation of action slips. Psychological Review, 88(1), 1-15.
Purves, D. (2011). Why we see what we do redux: a wholly empirical theory of vision:Sinauer Associates.
C. J. van Rijsbergen. (1979). Information Retrieval:Butterworths.
Rickman, R. M. (1996). Contentbased image retrieval using colour tuple histograms (2-7). Storage and Retrieval for Still Image and Video Databases IV, Proceedings of the Society of the Photo-Optical Instrumentation Engineers Vol. 2670, San Diego/La Jolla, CA, USA, March 1996.
Rui, Y. (2001). Relevance feedback techniques. In: Principles of Visual Information Retrieval:Springer- Verlag.
Rui, Y. (1999). Image retrieval: current techniques, promising directions, and open issues. Journal of Visual Communication and Image Representation, 10(1), 51-.
Smeulders, A. W. (2000). Content-based image retrieval at the end of the early years. IEEE Transaction on Pattern Analysis and Machine Intelligence, 22(12), 1349-1380.
Smith, J. R. (2002). Color for image retrieval. In: Principles of visual information retrieval:Springer-Verlag.
Smith, J. R. (1996). Tools and techniques for color image retrieval. Proceedings of IS&T/SPIE Symposium on Electronic Imaging: Science and Technology (EI’'96)―2 Storage and Retrieval for Image and Video Databases IV, 2670, 426-437.
Stricker, M. A. (1995). imilarity of color images (381-392). Storage and Retrieval for Image and Video Databases III, Proceedings of the Society of the Photo-Optical Instrumentation Engineers, Vol. 2420, San Diego/La Jolla, CA, USA, March 1995.
Swain, M. (1991). olor indexing. International Journal of Computer Vision, 7(1), 11-32.
Taylor, R. S. (1968). uestion-negotiation and information seeking in libraries. College and Research Libraries, 29, 178-194.
Veltkamp, R. C. (2002). survey of content-based image retrieval systems. in Content-Based Image and Video Retrieval:Kluwer.
Venters, C. C. (2000). review of content-based image retrieval systems. University of Manchester.
Venters, C. C. (2003). ind the gap: users interfaces and contentbased image retrieval. in Multimedia Systems and Content-Based Image Retrieval:Idea Publishing.
Yu, F.-X. (2011). olour image retrieval using pattern co-occurrence matrices based on BTC and VQ. Electronics Letters, 47(2), 100-101.
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