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A Probabilistic Method for Point Matching in the Presence of Noise and Degeneracy

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Abstract

The Bayesian method is widely used in image processing and computer vision to solve ill-posed problems. This is commonly achieved by introducing a prior which, together with the data constraints, determines a unique and hopefully stable solution. Choosing a “correct” prior is however a well-known obstacle.

This paper demonstrates that in a certain class of motion estimation problems, the Bayesian technique of integrating out the “nuisance parameters” yields stable solutions even if a flat prior on the motion parameters is used. The advantage of the suggested method is more noticeable when the domain points approach a degenerate configuration, and/or when the noise is relatively large with respect to the size of the point configuration.

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  1. Computer Science Department, Haifa University, Haifa, 31905, Israel

    Daniel Keren

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  1. Daniel Keren
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Correspondence to Daniel Keren.

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Keren, D. A Probabilistic Method for Point Matching in the Presence of Noise and Degeneracy. J Math Imaging Vis 33, 338–346 (2009). https://doi.org/10.1007/s10851-008-0116-z

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  • DOI: https://doi.org/10.1007/s10851-008-0116-z

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