The perspective projections of n physical points on two views (stereovision) are constrained as soon as n /spl ges/ 8. However, to prove, in practice, the existence of a rigid motion between two images, more than 8 point matches are desirable in order to compensate for the limited accuracy of the matches. We propose a computational definition of rigidity and a probabilistic criterion to rate the meaningfulness of a rigid set as a function of both the number of pairs of points (n) and the accuracy of the matches.. This criterion yields an objective way to compare, say, precise matches of a few points and approximate matches of a lot of points. It gives a yes/no answer to the question: "Could this rigid point correspondence have occurred by chance?", since it guarantees that the expected number of rigid sets found by chance in a random distribution of points is as small as desired. We use it to build an optimized random sampling algorithm that is able to detect a rigid motion and estimate the fundamental matrix when the set of point matches contains up to 90% of outliers, which outperforms classical methods like M-estimators, LMedS and RANSAC, known to break down around or before 50% of outliers.


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    Title :

    Automatic detection of rigid point matches


    Contributors:
    Moisan, L. (author) / Stival, B. (author)


    Publication date :

    2002-01-01


    Size :

    332567 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Automatic Detection of Rigid Point Matches

    Moisan, L. / Stival, B. | British Library Conference Proceedings | 2002