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Lattice Models for Context-Driven Regularization in Motion Perception

  • Silvio P. Sabatini
  • Fabio Solari
  • Giacomo M. Bisio
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2859)

Abstract

Real-world motion field patterns contain intrinsic statistic properties that allow to define Gestalts as groups of pixels sharing the same motion property. By checking the presence of such Gestalts in optic flow fields we can make their interpretation more confident. We propose a context-sensitive recurrent filter capable of evidencing motion Gestalts corresponding to 1st-order elementary flow components (EFCs). A Gestalt emerges from a noisy flow as a solution of an iterative process of spatially interacting nodes that correlates the properties of the visual context with that of a structural model of the Gestalt. By proper specification of the interconnection scheme, the approach can be straightforwardly extended to model any type of multimodal spatio-temporal relationships (i.e., multimodal spatiotemporal context).

Keywords

Motion Perception Process Equation Motion Segmentation Motion Property Distal Stimulus 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Haykin, S.: Adaptive Filter Theory. Prentice-Hall International Editions, Englewood Cliffs (1991)zbMATHGoogle Scholar
  2. 2.
    Koenderink, J.J.: Optic flow. Vision Res. 26(1), 161–179 (1986)CrossRefGoogle Scholar
  3. 3.
    Bar-Shalom, Y., Li, X.R.: Estimation and Tracking, Principles, Techniques, and Software. Artech House, Norwood (1993)zbMATHGoogle Scholar
  4. 4.
    Lucas, B., Kanade, T.: An iterative image registration technique with an application to stereo vision. In: Proc. DARPA Image Understanding Workshop, pp. 121–130 (1981)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Silvio P. Sabatini
    • 1
  • Fabio Solari
    • 1
  • Giacomo M. Bisio
    • 1
  1. 1.Department of Biophysical and Electronic EngineeringUniversity of GenovaGenovaItaly

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