Robust Detection and Affine Rectification of Planar Homogeneous Texture for Scene Understanding

Ahmad, Shahzor; Cheong, Loong-Fah

doi:10.1007/s11263-018-1078-2

Cited by 6 publications

(5 citation statements)

References 64 publications

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“…Several state-of-the-art methods can rectify from imaged coplanar repeated texture, but these methods assume the pinhole camera model [3], [16], [17], [18], [19], [20], [21], [22]. In particular, the method of Schaffalitzky et al [21] is the most similar to the solvers proposed in this paper since it also uses constraints induced by conjugate translations to recover the imaged scene-plane's vanishing line.…”

Section: Previous Workmentioning

confidence: 99%

“…Similar to the 3 point case, this introduces a one-dimensional family of false solutions. The matrix M has a similar structure as in (16) and again it is sufficient to saturate the top-left 2 × 2 cofactor. For this formulation we were able to create a solver with template size 14 × 18 (compared with 80 × 84 without using hidden-variable trick).…”

Section: One-direction Evp Solversmentioning

confidence: 99%

“…In this case, only 39 additional false solutions arise from the hidden-variable trick. The matrices M 1 and M 2 have a similar structure as in (16) and again it is sufficient to saturate the top-left 2 × 2 cofactors to remove the extra solutions. By saturating these determinants we were able to create a solver with template size 76 × 80 (previously 730 × 734).…”

Section: Two-direction Evp Solversmentioning

confidence: 99%

“…Several state-of-the-art methods can rectify from imaged coplanar repeated texture, but these methods assume the pinhole camera model [1,2,9,12,27,33,42]. A subset of these methods introduce solvers that use algebraic constraints induced by the equal-scale invariant of affine-rectified space [9,12,33] in a similar formulation to the proposed solvers (see Fig.…”

Section: Previous Workmentioning

confidence: 99%

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Minimal Solvers for Rectifying from Radially-Distorted Scales and Change of Scales

et al. 2020

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This paper introduces minimal solvers that jointly solve for affine-rectification and radial lens undistortion from the image of translated and reflected coplanar features. The proposed solvers use the invariant that the affine-rectified image of the meet of the joins of radially-distorted conjugately-translated point correspondences is on the line at infinity. The hidden-variable trick from algebraic geometry is used to reformulate and simplify the constraints so that the generated solvers are stable, small and fast. Multiple solvers are proposed to accommodate various local feature types and sampling strategies, and, remarkably, three of the proposed solvers can recover rectification and lens undistortion from only one radially-distorted conjugately-translated affine-covariant region correspondence. Synthetic and real-image experiments confirm that the proposed solvers demonstrate superior robustness to noise compared to the state of the art. Accurate rectifications on imagery taken with narrow to fisheye field-of-view lenses demonstrate the wide applicability of the proposed method. The method is fully automatic.

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Section: Previous Workmentioning

confidence: 99%

Section: One-direction Evp Solversmentioning

confidence: 99%

Section: Two-direction Evp Solversmentioning

confidence: 99%

Section: Previous Workmentioning

confidence: 99%

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Minimal Solvers for Rectifying from Radially-Distorted Scales and Change of Scales

et al. 2020

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“…Several state-of-the-art methods can rectify from imaged coplanar repeated texture, but these methods assume the pinhole camera model [5,8,9,10,17,18,19]. A subset of these methods use algebraic constraints induced by the equal-scale invariant of affinerectified space [8,9,10].…”

Section: Introductionmentioning

confidence: 99%

Rectification from Radially-Distorted Scales

Pritts

Kúkelová

Larsson

et al. 2019

Computer Vision – ACCV 2018

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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 Gröbner 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 if 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 strong assumptions about scene content made by the state of the art. Accurate rectifications on imagery taken with narrow focal length to fisheye lenses demonstrate the wide applicability of the proposed method. The method is automatic, and the code is published at https://github.com/prittjam/repeats.

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A Robust Automatic Method for Removing Projective Distortion of Photovoltaic Modules from Close Shot Images

Shen

Chen

Zhang

et al. 2020

Pattern Recognition and Computer Vision

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Robust Detection and Affine Rectification of Planar Homogeneous Texture for Scene Understanding

Cited by 6 publications

References 64 publications

Minimal Solvers for Rectifying from Radially-Distorted Scales and Change of Scales

Minimal Solvers for Rectifying from Radially-Distorted Scales and Change of Scales

Rectification from Radially-Distorted Scales

A Robust Automatic Method for Removing Projective Distortion of Photovoltaic Modules from Close Shot Images

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