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Motion correspondence through energy minimization

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Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1223))

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Abstract

The main aim of this work is to define a general algorithm to solve the well-known motion correspondence problem by minimizing an energy function where constraints leading to solution are defined. Starting from some approximated correspondences, estimated for features with high directional variance using radiometric similarity, optimal correspondence are obtained through an optimization technique. The new contribution of this work consists in the matching process based on refinement of raw measurements, in the energy function minimization technique converging to an optimal solution by taking advantage from some good initial guess, and in the applicability in a lot of contexts requiring motion correspondence just combining appropriate constraints functions. The approach has been tested in two common contexts: tracking of 3D coplanar points and passive navigation.

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Authors and Affiliations

  1. Istituto Elaborazione Segnali ed Immagini - C.N.R., Via Amendola 166/5, 70126, Bari, Italy

    A. Branca, E. Stella & A. Distante

Authors
  1. A. Branca
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  2. E. Stella
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  3. A. Distante
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Editor information

Marcello Pelillo Edwin R. Hancock

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© 1997 Springer-Verlag Berlin Heidelberg

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Branca, A., Stella, E., Distante, A. (1997). Motion correspondence through energy minimization. In: Pelillo, M., Hancock, E.R. (eds) Energy Minimization Methods in Computer Vision and Pattern Recognition. EMMCVPR 1997. Lecture Notes in Computer Science, vol 1223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62909-2_102

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  • DOI: https://doi.org/10.1007/3-540-62909-2_102

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-62909-2

  • Online ISBN: 978-3-540-69042-9

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