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Learning and Recognizing Structures in Façade Scenes (eTRIMS)—A Retrospective

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Abstract

Scene interpretation is the task of automatically creating descriptions for images. Such descriptions typically contain not only primitive objects but also structures that constitute primitive and structured objects. The learning and recognition of such structures was the objective of the EU project “eTraining for the Interpretation of Man-made Scenes (eTRIMS)”. The retrospective at hand presents main results of this project.

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References

  1. Neumann B (2008) Bayesian compositional hierarchies—a probabilistic structure for scene interpretation. Technical Report Memorandum FBI-HH-B-282/08, Department of Informatics, Hamburg University, University of Hamburg

  2. Šára R (2009) D4.4: performance evaluation. eTRIMS project deliverable

  3. Mitchell T (1978) Version spaces: an approach to concept learning. PhD thesis, Stanford University, Cambridge, MA

  4. Nagel HH (1988) From image sequences towards conceptual descriptions. Image Vis Comput 6(2):59–74

    Article  Google Scholar 

  5. Georis B, Mazière M, Brémond F, Thonnat M (2006) Evaluation and knowledge representation formalisms to improve video understanding. In: Proceedings of IEEE international conference on computer vision systems ICVS06, p 27

  6. Heintz F, Doherty P (2004) DyKnow: a framework for processing dynamic knowledge and object structures in autonomous systems. In: Proceedings of the international workshop on monitoring, security, and rescue techniques in multiagent systems (MSRAS)

  7. Schröder C, Neumann B (1996) On the logics of image interpretation: model-construction in a formal knowledge-representation framework. In: Proceedings ICIP-96, international conference on image processing, vol 2, pp 785–788

  8. Hotz L, Neumann B, Terzic K (2008) High-level expectations for low-level image processing. In: KI 2008: advances in artificial intelligence. LNCS, vol 5243. Springer, Berlin, pp 87–94

    Chapter  Google Scholar 

  9. Kreutzmann A, Terzic K, Neumann B (2009) Context-aware classification for incremental scene interpretation. In: Proceedings of the workshop on use of context in vision processing (UCVP 2009)

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Acknowledgements

This research has been supported by the European Community under the grant IST 027113, eTRIMS—eTraining for Interpreting Images of Man-Made Scenes.

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  1. HITeC c/o Departement Informatik, Universität Hamburg, 22527, Hamburg, Germany

    Lothar Hotz & Bernd Neumann

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  1. Lothar Hotz
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  2. Bernd Neumann
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Correspondence to Lothar Hotz.

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Hotz, L., Neumann, B. Learning and Recognizing Structures in Façade Scenes (eTRIMS)—A Retrospective. Künstl Intell 24, 63–68 (2010). https://doi.org/10.1007/s13218-010-0006-6

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