Abstract
Most of the currently existing image retrieval systems make use of either low-level features or semantic (textual) annotations. A combined usage during annotation and retrieval is rarely attempted. In this paper, we propose a standardized annotation framework that integrates semantic and feature based information about the content of images. The presented approach is based on the MPEG-7 standard with some minor extensions. The proposed annotation system SAFIRE (Semantic Annotation Framework for Image REtrieval) enables the combined use of low-level features and annotations that can be assigned to arbitrary hierarchically organized image segments. Besides the framework itself, we discuss query formalisms required for this unified retrieval approach.
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References
Bellman, R., Giertz, M.: On the Analytic Formalism of the Theory of Fuzzy Sets. Information Science 5, 149–156 (1973)
Bimbo, A.D.: Visual Information Retrieval. Morgan Kaufmann, San Francisco (1999)
Bloehdorn, S., et al.: Semantic annotation of images and videos for multimedia analysis. In: Gómez-Pérez, A., Euzenat, J. (eds.) ESWC 2005. LNCS, vol. 3532, Springer, Heidelberg (2005)
Boughanem, M., Loiseau, Y., Prade, H.: Rank-ordering documents according to their relevance in information retrieval using refinements of ordered-weighted aggregations. In: Adaptive Multimedia Retrieval: User, Context, and Feedback, Postproc. of 3rd Int. Workshop, pp. 44–54. Springer, Heidelberg (2006)
Boulgouris, N.V., et al.: Segmentation and content-based watermarking for color image and image region indexing and retrieval. EURASIP Journal on Applied Signal Processing, 418–431 (2002)
Carson, C., et al.: Blobworld: Image segmentation using expectation-maximization and its application to image querying. IEEE Trans. on Pattern Analysis and Machine Intelligence 24(8), 1026–1038 (2002)
Carson, C., et al.: Blobworld: A system for region-based image indexing and retrieval. In: Huijsmans, D.P., Smeulders, A.W.M. (eds.) VISUAL 1999. LNCS, vol. 1614, Springer, Heidelberg (1999)
Ciaccia, P., et al.: Imprecision and user preferences in multimedia queries: A generic algebraic approach. In: Schewe, K.-D., Thalheim, B. (eds.) FoIKS 2000. LNCS, vol. 1762, pp. 50–71. Springer, Heidelberg (2000)
Fagin, R.: Fuzzy Queries in Multimedia Database Systems. In: Proc. of the Seventeenth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, Seattle, Washington, June 1-3, 1998, pp. 1–10. ACM Press, New York (1998)
Feng, H., Chua, T.-S.: A bootstrapping approach to annotating large image collection. In: MIR ’03: Proc. of the 5th ACM SIGMM Int. Workshop on Multimedia Information Retrieval, Berkeley, California, pp. 55–62. ACM Press, New York (2003), doi:10.1145/973264.973274
Galindo, J., Urrutia, A., Piattini, M.: Fuzzy Databases: Modeling, Design and Implementation. Idea Group Publishing, Hershey (2005)
Hasida, K.: The linguistic DS: Linguisitic description in MPEG-7. The Computing Research Repository (CoRR), cs.CL/0307044 (2003)
Hollink, L., et al.: Semantic annotation of image collections. In: Proc. of Workshop on Knowledge Markup and Semantic Annotation (KCAP’03) (2003)
Jain, A.K., Dubes, R.C.: Algorithms for Clustering Data. Prentice Hall, New Jersey (1988)
Konishi, S., Yuille, A.L.: Statistical cues for domain specific image segmentation withperformance analysis. In: IEEE Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 125–132. IEEE Computer Society Press, Los Alamitos (2000)
Kosinov, S., Marchand-Maillet, S.: Overview of approaches to semantic augmentation of multimedia databases for efficient access and content retrieval. In: Adaptive Multimedia Retrieval, Postproc. of 1st Int. Workshop, pp. 19–35 (2004)
Lu, J., Ma, S.-p., Zhang, M.: Automatic image annotation based-on model space. In: Proc. of IEEE Int. Conf. on Natural Language Processing and Knowledge Engineering, pp. 455–460. IEEE Computer Society Press, Los Alamitos (2005)
Lux, M., Becker, J., Krottmaier, H.: Caliph & Emir: Semantic annotation and retrieval in personal digital photo libraries. In: Eder, J., Missikoff, M. (eds.) CAiSE 2003. LNCS, vol. 2681, pp. 85–89. Springer, Heidelberg (2003)
Martínez, J.M.: MPEG-7: Overview of MPEG-7 description tools, part 2. IEEE MultiMedia 9(3), 83–93 (2002)
Miller, G., et al.: Five papers on WordNet. Int. Journal of Lexicography 3(4) (1990)
Natsev, A.P., Naphade, M.R., Tesic, J.: Learning the Semantics of Multimedia Queries and Concepts from a Small Number of Examples. In: ACM Press (ed.) Proc. of the 13th ACM Int. Conf. on Multimedia, pp. 598–607. ACM Press, New York (2005)
Nürnberger, A., Detyniecki, M.: Adaptive multimedia retrieval: From data to user interaction. In: Do smart adaptive systems exist? - Best practice for selection and combination of intelligent methods, Springer, Heidelberg (2005)
Omhover, J.-F., Detyniecki, M.: Strict: An image retrieval platform for queries based on regional content. In: Enser, P.G.B., et al. (eds.) CIVR 2004. LNCS, vol. 3115, Springer, Heidelberg (2004)
Omhover, J.-F., Rifqi, M., Detyniecki, M.: Ranking invariance based on similarity measures in document retrieval. In: Adaptive Multimedia Retrieval: User, Context, and Feedback, Postproc. of 3rd Int. Workshop, pp. 55–64. Springer, Heidelberg (2006)
Rüger, S.: Putting the user in the loop: Visual resource discovery. In: Adaptive Multimedia Retrieval: User, Context, and Feedback, Postproc. of 3rd Int. Workshop, pp. 1–18. Springer, Heidelberg (2006)
Schmitt, I.: Basic Concepts for Unifying Queries of Database and Retrieval Systems. Technical Report 7, Fakultät für Informatik, Univ. Magdeburg (2005)
Schmitt, I., Schulz, N.: Similarity Relational Calculus and its Reduction to a Similarity Algebra. In: Seipel, D., Turull-Torres, J.M. (eds.) FoIKS 2004. LNCS, vol. 2942, pp. 252–272. Springer, Heidelberg (2004)
Schmitt, I., Schulz, N., Herstel, T.: WS-QBE: A QBE-like Query Language for Complex Multimedia Queries. In: Proc. of the 11th Int. Multimedia Modelling Conf (MMM’05), pp. 222–229. IEEE Computer Society Press, Los Alamitos (2005)
Schulz, N., Schmitt, I.: A Survey of Weighted Scoring Rules in Multimedia Database Systems. Preprint 7, Fakultät für Informatik, Univ. Magdeburg (2002)
Stauffer, C., Grimson, W.E.L.: Adaptive background mixture models for real-time tracking. In: Proc. IEEE Conf. on Computer Vision and Pattern Recognition, pp. 246–252. IEEE Computer Society Press, Los Alamitos (1999)
Veltkamp, R.C., Tanase, M.: Content-based image retrieval systems: A survey. Technical Report UU-CS-2000-34, CS Dept., Utrecht University (2000)
Voisine, N., et al.: A genetic algorithm-based approach to knowledge-assisted video analysis. In: IEEE International Conference on Image Processing, IEEE Computer Society Press, Los Alamitos (2005)
Vossen, P.: EuroWordNet general document version 3, final, July 19 (1999)
Zadeh, L.A.: Fuzzy Logic. IEEE Computer 21(4), 83–93 (1988)
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Hentschel, C., Nürnberger, A., Schmitt, I., Stober, S. (2007). SAFIRE: Towards Standardized Semantic Rich Image Annotation. In: Marchand-Maillet, S., Bruno, E., Nürnberger, A., Detyniecki, M. (eds) Adaptive Multimedia Retrieval: User, Context, and Feedback. AMR 2006. Lecture Notes in Computer Science, vol 4398. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71545-0_2
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DOI: https://doi.org/10.1007/978-3-540-71545-0_2
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