Abstract
This paper explores high-level scene interpretation with logic-based conceptual models. The main interest is in aggregates which describe interesting co-occurrences of physical objects and their respective views in a scene. Interpretations consist of instantiations of aggregate concepts supported by evidence from a scene. It is shown that flexible interpretation strategies are possible which are important for cognitive vision, e.g. mixed bottom-up and top-down interpretation, exploitation of context, recognition of intentions, task-driven focussing. The knowledge representation language is designed to easily map into a Description Logics (DL), however, current DL systems do not (yet) offer services which match high-level vision interpretation requirements. A table-laying scene is used as a guiding example. The work is part of the EU-project CogVis.
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References
Cohn, A.G., Hazarika, S.M.: Qualitative Spatial Representation and Reasoning: An Overview, Fundamenta Informaticae,46(1–2) (2001) 1–29
Vila, L.: A Survey on Temporal Reasoning in Artificial Intelligence”, AI Communications, Vol. 7, (1994) 4–28
Reiter, R., Mackworth, A.: The Logic of Depiction, TR 87-23, Dept. Computer Science, Univ. of British Columbia, Vancouver, Canada (1987)
Matsuyama, T., Hwang, V.S.: SIGMA — A Knowledge-Based Aerial Image Understanding System, Advances in Computer Vision and Machine Intelligence, Plenum (1990)
Schröder, C.: Bildinterpretation durch Modellkonstruktion: Eine Theorie zur rechnergestützten Analyse von Bildern, Dissertation, DISKI 196, infix (1999)
Nagel, H.-H.: From Video to Language — a Detour via Logic vs. Jumping to Conclusions, Proc. Integration of Speech and Image Understanding, IEEE Computer Society (1999) 79–99
Möller, R., Neumann, B., Wessel, M.: Towards Computer Vision with Description Logics: Some Recent Progress, Proc. Integration of Speech and Image Understanding, IEEE Computer Society (1999) 101–116
Barwise, J., Perry, J.: Situations and Attitudes, Bradford (1983)
Neumann, B.: Description of Time-Varying Scenes, Semantic Structures, Lawrence Erlbaum (1989) 167–206
Neumann, B.: Conceptual Framework for High-Level Vision, FBI-HH-B-241/02, FB Informatik, Universität Hamburg (2002)
Horrocks, I., Sattler, U., Tobies, S.: Reasoning with Individuals for the Description Logic SHIQ, Proc. 17th Int. Conf. on Automated Deduction (CADE-17). LNCS Springer (2002)
Haarslev, V., Möller, R.: RACER Userś Guide and Reference Manual Version 1.7, http://www.fh-wedel.de/~mo/3214/racer-manual-1-7.pdf
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Neumann, B., Weiss, T. (2003). Navigating through Logic-Based Scene Models for High-Level Scene Interpretations. In: Crowley, J.L., Piater, J.H., Vincze, M., Paletta, L. (eds) Computer Vision Systems. ICVS 2003. Lecture Notes in Computer Science, vol 2626. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36592-3_21
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DOI: https://doi.org/10.1007/3-540-36592-3_21
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