Language-based querying of image collections on the basis of an extensible ontology

Image and Vision Computing

Volumn 22, Issue 3, 2004, Pages 251-267

  Town, Christopher ^a   Sinclair, David ^b  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^b Waimara Ltd   (United Kingdom)

Author keywords

Image retrieval; Language parsing; Object recognition; Ontologies; Query languages

Indexed keywords

IMAGE ANALYSIS; IMAGE SEGMENTATION; OBJECT RECOGNITION; QUERY LANGUAGES; SEMANTICS;

LANGUAGE PARSING; ONTOLOGY;

IMAGE RETRIEVAL;

EID: 0742286855     PISSN: 02628856     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.imavis.2003.10.002     Document Type: Article

References (52)

1. Abella A., Kender J. From pictures to words: generating locative descriptions of objects in an image. ARPA94. 1994;II:909-II:918.
2. Aiello M., Areces C., de Rijke M. Spatial reasoning for image retrieval. In: Proceedings of International Workshop on Description Logics. 1999.
3. Bechhofer S., Goble C. Description logics and multimedia - applying lessons learnt from the Galen project. In: Proceedings of Workshop on Knowledge Representation for Interactive Multimedia Systems. 1996.
4. A. Bobick, W. Richards, Classifying objects from visual information, Technical report, MIT AI Lab, 1986.
5. Campbell N., Mackeown W., Thomas B., Troscianko T. Interpreting image databases by region classification. Pattern Recognition (Special Edition on Image Databases). 30:(4):1997;555-563.
6. Carson C., Belongie S., Greenspan H., Malik J. Region-based image querying. In: Proceedings of IEEE Workshop on Control-based Access of Image and Video Libraries. 1997.
7. Chang S., Chen W., Sundaram H. Semantic visual templates: linking visual features to semantics. In: Proceedings of Workshop on Content Based Video Search and Retrieval. 1998.
8. Chua T.-S., Teo K.-C., Ooi B.-C., Tan K.-L. Using domain knowledge in querying image databases. In: International Conference on Multimedia Modeling. 1996.
9. Cox I., Minka M., Minka T., Papathomas T., Yianilos P. The Bayesian image retrieval system, PicHunter. IEEE Transactions on Image Processing. 9:(1):2000;20-37.
10. Dobie M., Robert T., Joyce D., Weal M., Lewis P., Hall W. A flexible architecture for content and concept based multimedia information exploration. In: Proceedings of Second UK Conference on Image Retrieval. 1999.
11. Duygulu P., Barnard K., De Freitas J.F.H., Forsyth D.A. Object recognition as machine translation: learning a lexicon for a fixed image vocabulary. In: Proceedings of European Conference on Computer Vision. 2002.
12. Evans A., Thacker N., Mayhew J. The use of geometric histograms for model-based object recognition. In: Proceedings of British Machine Vision Conference. 1993.
13. Fensel D., Horrocks I., van Harmelen F., Decker S., Erdmann M., Klein M. OIL in a nutshell. In: Knowledge Acquisition, Modeling and Management. 2000;1-16.
14. Fung C., Loe K. A new approach for image classification and retrieval. In: Proceedings of ACM SIGIR Conference on Research and Development in Information Retrieval. 1999;ACM. pp. 301-302.
15. I. Glöckner, A. Knoll, Fuzzy quantifiers for processing natural-language queries in content-based multimedia, Technical Report TR97-05, Faculty of Technology, University of Bielefeld, Germany, 1997.
16. Gruber T. Towards principles for the design of ontologies used for knowledge sharing. Formal Ontology in Conceptual Analysis and Knowledge. 1993.
17. Gudivada V., Raghavan V. Content-based image retrieval systems. IEEE Computer. 28:(9):1995;18-22.
18. Hacid M., Rigotti C. Representing and reasoning on conceptual queries over image databases. In: Proceedings of the 11th International Symposium on Methodologies for Intelligent Systems, LNCS 1609, Springer, Berlin. 1999;. pp. 340-348.
19. Hsu C., Chu W., Taira R. A knowledge-based approach for retrieving images by content. Knowledge and Data Engineering. 8:(4):1996;522-532.
20. Hu W. An overview of the world wide web search technologies. In: Proceedings of SCI2001 - Fifth World Multi-conference on System, Cybernetics and Informatics. 2001.
21. ICON System. AT&T Laboratories Cambridge, www.uk.research.att.com/permm/icon.html.
22. Jaimes A., Chang S. Model-based classification of visual information for content-based retrieval. In: Proceedings of SPIE Conference on Storage and Retrieval for Image and Video Databases. 1999.
23. Kato T., Kurita T., Otsu N., Hirata K. A sketch retrieval method for full color image database query by visual example. In: Proceedings of International Conference on Pattern Recognition. 1992;I:530-I:533.
24. Kelly P., Cannon T., Hush D. Query by image example: the comparison algorithm for navigating digital image databases (CANDID) approach. In: Storage and Retrieval for Image and Video Databases (SPIE). 1995;238-248.
25. Lalmas M. Applications of uncertainty formalisms, chapter information retrieval and Dempster-Shafer's theory of evidence. 1998;Springer, Heidelberg. pp. 157-177.
26. J. Lim, Learnable visual keywords for image classification, In: Proceedings of ACM International Conference on Digital Libraries, 1999.
27. Miller G., Beckwith R., Fellbaum C., Gross D., Miller K. Introduction to Wordnet: an on-line lexical database. International Journal of Lexicography. 3:1990;235-244.
28. T. Mills, D. Pye, D. Sinclair, K. Wood, Shoebox: a digital photo management system, Technical report, AT&T Laboratories Cambridge, 1999.
29. Mojsilovic A., Gomes J., Rogowitz B. Isee: perceptual features for image library navigation. In: Proceedings of SPIE Human Vision and Electronic Imaging. 2002.
30. Mueller H., Marchand-Maillet S., Pun T. The truth about corel - evaluation in image retrieval. In: Proceedings of Conference on Image and Video Retrieval, LNCS 2383, Springer, Berlin. 2002;. pp. 38-50.
31. Mueller H., Mueller W., McG Squire D., Marchand-Maillet S., Pun T. Performance evaluation in content-based image retrieval: overview and proposals. Pattern Recognition Letters. 22:(5):2001;593-601.
32. Nepal S., Ramakrishna M., Thom J. A fuzzy object query language (foql) for image databases. In: Sixth International Conference on Database Systems for Advanced Applications. 1999.
33. W. Niblack, The qbic project: querying images by color, texture and shape, Technical report, IBM Research Report RJ-9203, 1993.
34. Ogle V., Stonebraker M. Chabot: retrieval from a relational database of images. IEEE Computer. 28:(9):1995;40-48.
35. Parsons S., Hunter A. Applications of uncertainty formalisms. A Review of Uncertainty Handling Formalisms. 1998;Springer, Berlin. pp. 8-37, Chapter A.
36. Petrakis G.M. Design and evaluation of spatial similarity approaches for image retrieval. Image and Vision Computing. 20:2002;59-76.
37. K. Rodden, How do people organise their photographs? In: BCS IRSG 21st Annual Colloquium on Information Retrieval Research, 1999.
38. Roussoupolos N., Falautsos C., Sellis T. An efficient pictorial database system for psql. IEEE Transactions on Software Engineering. 14:(5):1988;639-659.
39. Rucklidge W. Locating objects using the hausdorff distance. In: Proceedings of International Conference on Computer Vision. 1995.
40. Rui Y., Huang T., Chang S. Image retrieval: current techniques, promising directions and open issues. Journal of Visual Communication and Image Representation. 10:1999;39-62.
41. Santini S., Gupta A., Jain R. Emergent semantics through interaction in image databases. Knowledge and Data Engineering. 13:(3):2001;337-351.
42. Shen H., Ooi K., Tan B. Finding semantically related images in the WWW. In: Proceedings of ACM Multimedia. 2000;. pp. 491-492.
43. D. Sinclair, Voronoi seeded colour image segmentation, Technical Report TR99-04, AT&T Laboratories Cambridge, 1999.
44. Sinclair D. Smooth region structure: folds, domes, bowls, ridges, valleys and slopes. In: Proceedings of Conference on Computer Vision and Pattern Recognition. 2000;IEEE Computer Society Press, Silver Spring, MD. pp. 389-394.
45. Smeulders A., Worring M., Santini S., Gupta A., Jain R. Content-based image retrieval at the end of the early years. IEEE Transactions on Pattern Analysis and Machine Intelligence. 22:(12):2000;1349-1380.
46. Smith J., Chang S. Image and video search engine for the world wide web. In: Storage and Retrieval for Image and Video Databases (SPIE). 1997;84-95.
47. Sparck Jones K. Information retrieval and artificial intelligence. Artificial Intelligence. 114:1999;257-281.
48. Tieu K., Viola P. Boosting image retrieval. In: Proceedings of International Conference on Computer Vision. 2000.
49. C.P. Town, D.A. Sinclair, Content based image retrieval using semantic visual categories, Technical Report MV01-211, Society for Manufacturing Engineers, 2001.
50. Vasconcelos N., Lippman A., Bayesian A. A Bayesian framework for content-based indexing and retrieval. In: Proceedings of Conference on Computer Vision and Pattern Recognition. 1998.
51. Wenyin L., Dumais S., Sun Y., Zhang H., Czerwinski M., Field B. Semi-automatic image annotation. In: Proceedings of Interact Conference on Human Computer Interaction. 2001;2001.
52. Wood M., Campbell N., Thomas B. Iterative refinement by relevance feedback in content-based digital image retrieval. In: Proceedings of ACM Multimedia 98. 1998;13-17.