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Distributing Inferential Activity for Synchronic and Diachronic Data Fusion

  • Conference paper
Multisensor Fusion for Computer Vision

Part of the book series: NATO ASI Series ((NATO ASI F,volume 99))

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Abstract

Multisensor fusion may be suitable at a variety of levels: from the preprocessed signal up to the symbolic level in which partial models of the environment are expressed. This paper addresses the problem of fusing together pieces of information at etherogeneous levels. This problem is encountered while integrating new sensor information with an already constructed symbolic model. These pieces of information can even derive from “snapshots” taken at different times.

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References

  1. Fischler, Bolles, — “Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography”, — Communications of the ACM, Vol. 24, n. 6, pp. 381–395, (1981)

    MathSciNet  Google Scholar 

  2. Gu, Yang, Huang, — “Matching perspective views of polyhedra using circuits” — IEEE Transactions on PAMI, Vol. 9, n. 3, pp. 390–400, (1987)

    Google Scholar 

  3. Canny, — “A computational approach to edge detection”, — IEEE Transactions on PAMI, Vol. 8, n. 6, pp. 679–698, (1986)

    Google Scholar 

  4. Lowe, — “Three dimensional object recognition from single two dimensional images” Artificial Intelligence Journal, Vol. 31, pp. 355–395, (1987)

    Google Scholar 

  5. Caglioti, — “The corner plus point perspective problem with applications to the recognition of planar patterns”, — submitted for publication

    Google Scholar 

  6. Gordon, Seering — “Real-time Part Position Sensing” — IEEE Transactions on PAMI, Vol. 10, n. 3, pp. 374–385, (1988)

    Google Scholar 

  7. Durrant-White, — “Integration, Coordination, and Control of Multi Sensor Robot Systems”, — Kluwer Academic Publisher, (1987)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Artificial Intelligence and Robotics Project Dipartimento di Elettronica, Politecnico di Milano, P.za Leonardo da Vinci, 32, 20133, Milano, Italy

    V. Caglioti & M. Somalvico

Authors
  1. V. Caglioti
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  2. M. Somalvico
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Editor information

Editors and Affiliations

  1. Computer and Vision Research Center Department of Electrical and Computer Engineering, The University of Texas at Austin, 78712-1084, Austin, TX, USA

    J. K. Aggarwal (Director) (Director)

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© 1993 Springer-Verlag Berlin Heidelberg

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Caglioti, V., Somalvico, M. (1993). Distributing Inferential Activity for Synchronic and Diachronic Data Fusion. In: Aggarwal, J.K. (eds) Multisensor Fusion for Computer Vision. NATO ASI Series, vol 99. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-02957-2_16

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  • DOI: https://doi.org/10.1007/978-3-662-02957-2_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-08135-4

  • Online ISBN: 978-3-662-02957-2

  • eBook Packages: Springer Book Archive

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