4,499 research outputs found
Image Segmentation with Multidimensional Refinement Indicators
We transpose an optimal control technique to the image segmentation problem.
The idea is to consider image segmentation as a parameter estimation problem.
The parameter to estimate is the color of the pixels of the image. We use the
adaptive parameterization technique which builds iteratively an optimal
representation of the parameter into uniform regions that form a partition of
the domain, hence corresponding to a segmentation of the image. We minimize an
error function during the iterations, and the partition of the image into
regions is optimally driven by the gradient of this error. The resulting
segmentation algorithm inherits desirable properties from its optimal control
origin: soundness, robustness, and flexibility
Rectification from Radially-Distorted Scales
This paper introduces the first minimal solvers that jointly estimate lens
distortion and affine rectification from repetitions of rigidly transformed
coplanar local features. The proposed solvers incorporate lens distortion into
the camera model and extend accurate rectification to wide-angle images that
contain nearly any type of coplanar repeated content. We demonstrate a
principled approach to generating stable minimal solvers by the Grobner basis
method, which is accomplished by sampling feasible monomial bases to maximize
numerical stability. Synthetic and real-image experiments confirm that the
solvers give accurate rectifications from noisy measurements when used in a
RANSAC-based estimator. The proposed solvers demonstrate superior robustness to
noise compared to the state-of-the-art. The solvers work on scenes without
straight lines and, in general, relax the strong assumptions on scene content
made by the state-of-the-art. Accurate rectifications on imagery that was taken
with narrow focal length to near fish-eye lenses demonstrate the wide
applicability of the proposed method. The method is fully automated, and the
code is publicly available at https://github.com/prittjam/repeats.Comment: pre-prin
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