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A Framework for Generic State Estimation in Computer Vision Applications

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Book cover Computer Vision Systems (ICVS 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2095))

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Abstract

Experimenting and building integrated, operational systems in computational vision poses both theoretical and practical challenges, involving methodologies from control theory, statistics, optimization, computer graphics, and interaction. Consequently, a control and communication structure is needed to model typical computer vision applications and a flexible architecture is necessary to combine the above mentioned methodologies in an effective implementation. In this paper, we propose a three-layer computer vision framework that offers: a) an application model able to cover a large class of vision applications; b) an architecture that maps this model to modular, flexible and extensible components by means of object-oriented and dataflow mechanisms; and c) a concrete software implementation of the above that allows construction of interactive vision applications. We illustrate how a variety of vision techniques and approaches can be modeled by the proposed framework and we present several complex, application oriented, experimental results.

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Author information

Authors and Affiliations

  1. Institut National Polytechnique de Grenoble, INRIA Rhône-Alpes, France

    Cristian Sminchisescu

  2. Dept. of Mathematics and Computer Science, Eindhoven University of Technology, The Netherlands

    Alexandru Telea

Authors
  1. Cristian Sminchisescu
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  2. Alexandru Telea
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Editor information

Editors and Affiliations

  1. ETH Zentrum, IFW B26.1, 8092, Zürich, Switzerland

    Bernt Schiele

  2. Technische Fakultät, Angewandte Informatik, Universität Bielefeld, Postfach 100 131, 33501, Bielefeld, Germany

    Gerhard Sagerer

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© 2001 Springer-Verlag Berlin Heidelberg

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Sminchisescu, C., Telea, A. (2001). A Framework for Generic State Estimation in Computer Vision Applications. In: Schiele, B., Sagerer, G. (eds) Computer Vision Systems. ICVS 2001. Lecture Notes in Computer Science, vol 2095. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48222-9_2

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  • DOI: https://doi.org/10.1007/3-540-48222-9_2

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42285-3

  • Online ISBN: 978-3-540-48222-2

  • eBook Packages: Springer Book Archive

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