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Robust Non-parametric Data Fitting for Correspondence Modeling | IEEE Conference Publication | IEEE Xplore

Robust Non-parametric Data Fitting for Correspondence Modeling


Abstract:

We propose a generic method for obtaining nonparametric image warps from noisy point correspondences. Our formulation integrates a huber function into a motion coherence ...Show More

Abstract:

We propose a generic method for obtaining nonparametric image warps from noisy point correspondences. Our formulation integrates a huber function into a motion coherence framework. This makes our fitting function especially robust to piecewise correspondence noise (where an image section is consistently mismatched). By utilizing over parameterized curves, we can generate realistic nonparametric image warps from very noisy correspondence. We also demonstrate how our algorithm can be used to help stitch images taken from a panning camera by warping the images onto a virtual push-broom camera imaging plane.
Date of Conference: 01-08 December 2013
Date Added to IEEE Xplore: 03 March 2014
Electronic ISBN:978-1-4799-2840-8

ISSN Information:

Conference Location: Sydney, NSW, Australia

References

References is not available for this document.