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Stereo matching using M-estimators

  • Stereo and Correspondence
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Book cover Computer Analysis of Images and Patterns (CAIP 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1296))

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Abstract

Stereo computation is just one of the vision problems where the presence of outliers cannot be neglected. Most standard algorithms make unrealistic assumptions about noise distributions, which leads to erroneous results that cannot be corrected in subsequent processing stages. In this work the standard area-based correlation approach is modified so that it can tolerate a significant number of outliers. The approach exhibits a robust behaviour not only in the presence of mismatches but also in the case of depth discontinuities. Experimental results are given on synthetic and real images.

This work was supported by a grant from the Austrian National Fonds zur Förderung der wissenschaftlichen Forschung (No. S7002MAT) and (No. P9110-SPR).

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Author information

Authors and Affiliations

  1. Pattern Recognition and Image Processing Group, Vienna University of Technology, Treitlstraße 3/183/2, Vienna, Austria

    Christian Menard & Aleš Leonardis

  2. Faculty of Computer and Information Science, University of Ljubljana, Ljubljana

    Aleš Leonardis

Authors
  1. Christian Menard
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  2. Aleš Leonardis
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Editor information

Gerald Sommer Kostas Daniilidis Josef Pauli

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© 1997 Springer-Verlag Berlin Heidelberg

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Menard, C., Leonardis, A. (1997). Stereo matching using M-estimators. In: Sommer, G., Daniilidis, K., Pauli, J. (eds) Computer Analysis of Images and Patterns. CAIP 1997. Lecture Notes in Computer Science, vol 1296. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63460-6_131

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  • DOI: https://doi.org/10.1007/3-540-63460-6_131

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63460-7

  • Online ISBN: 978-3-540-69556-1

  • eBook Packages: Springer Book Archive

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