Abstract
Automating the steps involved in video processing has yet to be tackled with much success by vision developers and knowledge engineers. This is due to the difficulty in formulating vision problems and their solutions in a generalised manner. In this collaborated work, we introduce a modular approach that utilises ontologies to capture the goals, domain description and capabilities for performing video analysis. This modularisation is tested on real-world videos from an ecological source and proves useful in conceptualising and generalising video processing tasks. On a more significant note, this could be used in a framework for automatic video analysis in emerging infrastructures such as the Grid.
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References
Gomez-Perez, A., Fernandez-Lopez, M., Corcho, O.: Ontological Engineering: With Examples from the Areas of Knowledge Management, E-Commerce and the Semantic Web (1st edn.) (2004)
Nouvel, A., Dalle, P.: An Interactive Approach For Image Ontology Definition. In: 13ème Congrès de Reconnaissance des Formes et Intelligence Artificielle, Angers, France, pp. 1023–1031 (2002)
Maillot, N., Thonnat, M., Boucher, A.: Towards Ontology Based Cognitive Vision (Long Version). Machine Vision and Applications 16(1), 33–40 (2004)
Bombardier, V., Lhoste, P., Mazaud, C.: Modélisation et intégration de connaissances métier pour l’identification de défauts par règles linguistiques floues. Traitement du Signal 21(3), 227–247 (2004)
Hudelot, C.: Towards a Cognitive Vision Platform for Semantic Image Interpretation. Application to the Recognition of Biological Organisms. PhD thesis, Nice-Sophia Antipolis University (2005)
Town, C.: Ontological Inference for Image and Video Analysis. Mach. Vision Appl. 17(2), 94–115 (2006)
McGuinness, D., van Harmelen, F.: OWL Web Ontology Language. World Wide Web Consortium (W3C) (2004), http://www.w3.org/TR/owl-features/
Matsuyama, T.: Expert Systems for Image Processing: Knowledge-Based Composition of Image Analysis Processes. CVGIP 48(1), 22–49 (1989)
Renouf, A., Clouard, R., Revenu, M.: How to Formulate Image Processing Applications? In: Proceedings of the International Conference on Computer Vision Systems, Bielefeld, Germany (2007)
EcoGrid National Center for High Performance Computing, Taiwan. http://ecogrid.nchc.org.tw/
Nadarajan, G., Chen-Burger, Y.H., Malone, J.: Semantic-Based Workflow Composition for Video Processing in the Grid. In: IEEE/WIC/ACM International Conference on Web Intelligence, pp. 161–165 (2006)
Foster, I.: The Grid 2 – Blueprint for a New Computing Infrastructure, 2nd edn. Morgan Kaufmann, San Francisco (2004)
Liedtke, C., Blömer, A.: Architecture of the Knowledge Based Configuration System for Image Analysis ”Conny”. In: ICPR 1992, pp. 375–378 (1992)
Clément, V., Thonnat, M.: A Knowledge-Based Approach to Integration of Image Procedures Processing. CVGIP: Image Understanding 57(2), 166–184 (1993)
Chien, S., Mortensen, H.: Automating Image Processing for Scientific Data Analysis of a large Image Database. IEEE PAMI 18(8), 854–859 (1996)
Clouard, R., Elmoataz, A., Porquet, C., Revenu, M.: Borg: A Knowledge-Based System for Automatic Generation of Image Processing Programs. IEEE PAMI 21(2), 128–144 (1999)
Draper, B., Hanson, A., Riseman, E.: Knowledge-directed vision: Control, learning, and integration. Proc. of IEEE 84, 1625–1681 (1996)
Bloehdorn, S., Petridis, K., Saathoff, C., Simou, N., Tzouvaras, V., Avrithis, Y., Handschuh, S., Kompatsiaris, Y., Staab, S., Strintzis, M.G.: Semantic Annotation of Images and Videos for Multimedia Analysis. In: Gómez-Pérez, A., Euzenat, J. (eds.) ESWC 2005. LNCS, vol. 3532, pp. 592–607. Springer, Heidelberg (2005)
Renouf, A.: (Hermès - a human-machine interface for the formulation of image processing applications), http://www.greyc.ensicaen.fr/~arenouf/Hermes
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Nadarajan, G., Renouf, A. (2007). A Modular Approach for Automating Video Analysis. In: Kropatsch, W.G., Kampel, M., Hanbury, A. (eds) Computer Analysis of Images and Patterns. CAIP 2007. Lecture Notes in Computer Science, vol 4673. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74272-2_17
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DOI: https://doi.org/10.1007/978-3-540-74272-2_17
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