Planar surface orientation from texture spatial frequencies

Super, Boaz J.; Bovik, Alan C.

doi:10.1016/0031-3203(94)00140-h

Cited by 80 publications

(108 citation statements)

References 16 publications

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“…When viewed from the standpoint of shape recovery, there are two distinct areas of activity in the literature. The first of these confines its attention to planar surfaces and focuses on the recovery of perspective geometry from texture gradient or vanishing point location [4], [5], [6], [7]. The second problem is that of interpreting the geometry of curved surfaces [8], [9], [10], [11], [12].…”

Section: Introductionmentioning

confidence: 99%

“…We follow Krumm and Shafer [13], Super and Bovik [5], [14], Malik and Rosenholtz [10], [11] by measuring the local texture variations due to the perspectivity using the frequency domain affine distortion of the pattern of spectral peaks. Our main contribution is to show that the directions of the eigenvectors of the affine distortion matrix can be used to directly estimate the slant and tilt angles of local tangent planes to curved surfaces.…”

Section: Introductionmentioning

confidence: 99%

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Shape from periodic texture using the eigenvectors of local affine distortion

Ribeiro

Hancock

2001

IEEE Trans. Pattern Anal. Machine Intell.

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AbstractÐThis paper shows how the local slant and tilt angles of regularly textured curved surfaces can be estimated directly, without the need for iterative numerical optimization. We work in the frequency domain and measure texture distortion using the affine distortion of the pattern of spectral peaks. The key theoretical contribution is to show that the directions of the eigenvectors of the affine distortion matrices can be used to estimate local slant and tilt angles of tangent planes to curved surfaces. In particular, the leading eigenvector points in the tilt direction. Although not as geometrically transparent, the direction of the second eigenvector can be used to estimate the slant direction. The required affine distortion matrices are computed using the correspondences between spectral peaks, established on the basis of their energy ordering. We apply the method to a variety of real-world and synthetic imagery.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Shape from periodic texture using the eigenvectors of local affine distortion

Ribeiro

Hancock

2001

IEEE Trans. Pattern Anal. Machine Intell.

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“…Our method shares with Krumm and Shafer [9] and Super and Bovik [10,20] the feature of using the affine distortion of spectra to estimate surface orientation. However, these two methods recover surface orientation by exhaustive spectral back-projection and error enumeration for all slant and tilt angles.…”

Section: Computing Local Planar Orientationmentioning

confidence: 98%

“…To overcome this difficulty it is usual to use a linear approximation of the perspective projection [9,10]. This affine approximation captures the local translation, rotation and skew of the texture, but does not capture the foreshortening effect.…”

Section: Geometric Modellingmentioning

confidence: 99%

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Detecting multiple texture planes using local spectral distortion

Ribeiro

Robles-Kelly

Hancock

2002

Image and Vision Computing

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This paper presents a spectral method for identifying multiple texture planes. We commence by showing how pairs of spectral peaks can be used to make direct estimates of the slant and tilt angles. Our method commences by computing the affine distortion matrices for pairs of corresponding spectral peaks. We show that the directions of the eigenvectors of the affine distortion matrices can be used to estimate local planar pose. The leading eigenvector points in the tilt direction and the direction of the second eigenvector can be used to estimate the slant direction. By searching for clusters in the computed slant and tilt angles, we locate multiple texture planes. We apply the method to a variety of real-world and synthetic imagery. q

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Estimation of rotation and slant angles of a textured plane using spectral moments

Tsuji

Yoshida

2003

Systems & Computers in Japan

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This paper proposes a method for estimating rotation and slant angles with slant direction of a textured plane using spectral moments. When a textured plane rotates and slants, the 2D power spectrum also rotates and expands toward the slant direction. Thus, the spectral moments also change corresponding to the rotation and expansion. The rotation angle, slant angle, and slant direction of a textured plane can be derived from the comparison between the second-order spectral moments of a standard image and those of a test image. We show the validity of the method in simulations using the synthesized images and in experiments using real images taken with a CCD camera.

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Planar surface orientation from texture spatial frequencies

Cited by 80 publications

References 16 publications

Shape from periodic texture using the eigenvectors of local affine distortion

Shape from periodic texture using the eigenvectors of local affine distortion

Detecting multiple texture planes using local spectral distortion

Estimation of rotation and slant angles of a textured plane using spectral moments

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