Robust Image Matching under a Large Disparity

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Author(s)

Abstract

We present a new method for detecting point matches between two images without using any combinatorial search. Our strategy is to impose various local and non-local constraints as "soft" constraints by introducing their "confidence" measures via "mean-field approximations". The computation is a cascade of evaluating the confidence values and sorting according to them. In the end, we impose the "hard" epipolar constraint by RANSAC. We also introduce a model selection procedure to test if the image mapping can be regarded as a homography. We demonstrate the effectiveness of our method by real image examples.

Journal

  • Memoirs of the Faculty of Engineering, Okayama University

    Memoirs of the Faculty of Engineering, Okayama University 37(1), 25-32, 2002-11

    Faculty of Engineering, Okayama University

Codes

  • NII Article ID (NAID)
    80015664456
  • NII NACSIS-CAT ID (NCID)
    AA10699856
  • Text Lang
    ENG
  • Article Type
    departmental bulletin paper
  • ISSN
    0475-0071
  • Data Source
    IR 
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