Abstract
Current solutions are still far from reaching the ultimate goal, namely to enable users to retrieve the desired video clip among massive amounts of visual data in a semantically meaningful manner. With this study we propose a video database model that provides nearly automatic object, event and concept extraction. It provides a reasonable approach to bridging the gap between low-level representative features and high-level semantic contents from a human point of view. By using training sets and expert opinions, low-level feature values for objects and relations between objects are determined. At the top level we have an ontology of objects, events and concepts. Objects and/or events use all these information to generate events and concepts. The system has a reliable video data model, which gives the user the ability to make ontology-supported fuzzy querying. Queries containing objects, events, spatio-temporal clauses, concepts and low-level features can be handled.
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References
Berkeley db xml web site, http://www.sleepycat.com
Xquery web site, http://www.w3.org/XML/Query
Bao, J., et al.: Integration of domain-specific and domain-independent ontologies for colonoscopy video database annotation. In: International Conference on Information and Knowledge Engineering (IKE 04) (2004)
Chang, S.-F., et al.: A fully automated content-based video search engine supporting spatio-temporal queries. IEEE Transactions on Circuits and Systems for Video Technology (CSVT) 8(5), 602–615 (1998)
Deng, Y., Mukherjee, D., Manjunath, B.S.: Netra-v: Toward an object-based video representation. In: Storage and Retrieval for Image and Video Databases (SPIE), pp. 202–215 (1998)
Donderler, M.E.: Data Modeling and Querying for Video Databases. PhD thesis, Bilkent University, Turkey (2002)
Fan, J., Zhu, X., Xiao, J.: Content-based video indexing and retrieval. In: SPIE Proceed. V., vol. 4315 (2002)
Fan, J., et al.: Multiview: Multilevel video content representation and retrieval. Journal of Electronic Imaging 10(4), 895–908 (2001)
Flickner, M., et al.: Query by image and video content: The qbic system. Computer 28(9), 23–32 (1995)
Haav, H.M.: A survey of concept-based information retrieval tools on the web. In: Caplinskas, A., Eder, J. (eds.) ADBIS 2001. LNCS, vol. 2151, pp. 29–41. Springer, Heidelberg (2001)
Hammiche, S., et al.: Semantic retrieval of multimedia data. In: MMDB ’04: Proceedings of the 2nd ACM international workshop on Multimedia databases, Washington, DC, USA, pp. 36–44. ACM Press, New York (2004)
Koprulu, M., Cicekli, N.K., Yazici, A.: Spatio-temporal querying in video databases. In: FQAS, pp. 251–262 (2002)
Lee, J., Oh, J.-H., Hwang, S.: Strg-index: Spatio-temporal region graph indexing for large video databases. In: SIGMOD Conference, pp. 718–729 (2005)
Luo, J., Etz, S.P.: A physical model-based approach to detecting sky in photographic images. IEEE Transactions on Image Processing 11(3), 201–212 (2002)
Nevatia, R., Hobbs, J., Bolles, B.: An ontology for video event representation. In: Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW’04), vol. 7, Washington, DC, USA, p. 119. IEEE Computer Society Press, Los Alamitos (2004)
Petkovic, M., Jonker, W.: An overview of data models and query languages for content-based video retrieval. In: International Conference on Advances in Infrastructure for Electronic Business, Science, and Education on the Internet, l‘Aquila, Italy (2000)
Petkovic, M., Jonker, W.: Content-based retrieval of spatio-temporal video events. In: Proceedings International Conference Managing Information Technology in a Global Economy, Toronto, Canada (2001)
Smeulders, A.W.M., et al.: Content-based image retrieval at the end of the early years. IEEE Trans. Pattern Anal. Mach. Intell. 22(12), 1349–1380 (2000), doi:10.1109/34.895972
Spyns, P., Meersman, R., Jarrar, M.: Data modelling versus ontology engineering. SIGMOD Rec. 31(4), 12–17 (2002)
Wei, W., Ngan, K.N.: Automatic video object segmentation for mpeg-4. In: VCIP, pp. 9–19 (2003)
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Yildirim, Y., Yazici, A. (2007). Ontology-Supported Video Modeling and Retrieval. 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_3
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DOI: https://doi.org/10.1007/978-3-540-71545-0_3
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