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7,421
Grouping Curved Lines
 Machine Graphics and Vision 7
, 1994
"... This paper examines the problem of automatically grouping image curves. In contrast, most previous work has been restricted to points and straight lines. Some of the computational aspects of the groupings of continuation, parallelism, and proximity are analysed, and the issues of neighbourhoods, ..."
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Cited by 8 (0 self)
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This paper examines the problem of automatically grouping image curves. In contrast, most previous work has been restricted to points and straight lines. Some of the computational aspects of the groupings of continuation, parallelism, and proximity are analysed, and the issues of neighbourhoods
Grouping Curved Lines
 Machine Graphics and Vision 7
, 1994
"... This paper examines the problem of automatically grouping image curves. ..."
Principal Curves
, 1989
"... Principal curves are smooth onedimensional curves that pass through the middle of a pdimensional data set, providing a nonlinear summary of the data. They are nonparametric, and their shape is suggested by the data. The algorithm for constructing principal curve starts with some prior summary, suc ..."
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Cited by 394 (1 self)
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, such as the usual principalcomponent line. The curve in each successive iteration is a smooth or local average of the pdimensional points, where the definition of local is based on the distance in arc length of the projections of the points onto the curve found in the previous iteration. In this article principal
On active contour models and balloons
 CVGIP: Image
"... The use.of energyminimizing curves, known as “snakes, ” to extract features of interest in images has been introduced by Kass, Witkhr & Terzopoulos (Znt. J. Comput. Vision 1, 1987,321331). We present a model of deformation which solves some of the problems encountered with the original method. ..."
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Cited by 588 (43 self)
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. The external forces that push the curve to the edges are modified to give more stable results. The original snake, when it is not close enough to contours, is not attracted by them and straightens to a line. Our model makes the curve behave like a balloon which is inflated by an additional force. The initial
Extraction of Curved Lines from Images
 In 13th International Conference on Pattern Recognition
, 1996
"... In this paper a method to extract curvilinear structures and their widths from digital images is presented. The approach is based on differential geometric properties of the image function. For each pixel, the second order Taylor polynomial is computed by convolving the image with the derivatives of ..."
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Cited by 12 (2 self)
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of a Gaussian smoothing kernel. Line points are required to have a vanishing gradient and a high curvature in the direction perpendicular to the line. The resulting filter generates a single response for each line. The line position can be determined with subpixel accuracy and the algorithm scales
Recovering specular surfaces using curved line images
 In CVPR ’09. 2
"... We present a new shapefromdistortion framework for recovering specular (reflective/refractive) surfaces. While most existing approaches rely on accurate correspondences between 2D pixels and 3D points, we focus on analyzing the curved images of 3D lines which we call curved line images or CLIs. Ou ..."
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Cited by 8 (3 self)
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We present a new shapefromdistortion framework for recovering specular (reflective/refractive) surfaces. While most existing approaches rely on accurate correspondences between 2D pixels and 3D points, we focus on analyzing the curved images of 3D lines which we call curved line images or CLIs
Improved Curvature and Anisotropy Estimation for Curved Line Bundles
"... The gradientsquare tensor describes the orientation dependence of the squared directional derivative in images. The ratio of eigenvalues is a measure of local anisotropy. For an area showing shift invariance along some orientation (think of a piece of straight rail track) one of the tensor eigenval ..."
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eigenvalues is zero. In practical situations (think of a piece of curved rail track) rotation invariance (perhaps around a remote center) occurs more often than shift invariance. Then curvature contributes to the smallest eigenvalue. In order to avoid this we deform a local area in such a way
Visual discrimination, categorical identification, and categorical rating in brief displays of curved lines: implications for discrete encoding processes
 Journal of Experimental Psychology: Human Perception and Performance
, 1983
"... Visual discrimination, categorical identification, and categorical rating measurements were made on sets of curvedline stimuli drawn from a theoretically uniform continuum with curvature parameter s. In Experiment 1, discriminability of pairs of curved lines separated by a constant distance on the. ..."
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Cited by 11 (6 self)
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Visual discrimination, categorical identification, and categorical rating measurements were made on sets of curvedline stimuli drawn from a theoretically uniform continuum with curvature parameter s. In Experiment 1, discriminability of pairs of curved lines separated by a constant distance on the
Publ. Mat. 47 (2003), 415–440 MEAN DIRECTIONALLY CURVED LINES ON SURFACES IMMERSED IN R4
"... The notion of principal configuration of immersions of surfaces into R3, due to Sotomayor and Gutierrez [16] for lines of curvature and umbilics, is extended to that of mean directional configuration for immersed surfaces in R4. This configuration consists on the families of mean directionally curve ..."
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curved lines, along which the second fundamental form points in the direction of the mean curvature vector, and their singularities, called here Hsingularities. The concepts of Hsingularities and periodic mean directionally curved lines are studied here in detail. Also the notion of principal
A New Point Matching Algorithm for NonRigid Registration
, 2002
"... Featurebased methods for nonrigid registration frequently encounter the correspondence problem. Regardless of whether points, lines, curves or surface parameterizations are used, featurebased nonrigid matching requires us to automatically solve for correspondences between two sets of features. I ..."
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Cited by 356 (3 self)
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Featurebased methods for nonrigid registration frequently encounter the correspondence problem. Regardless of whether points, lines, curves or surface parameterizations are used, featurebased nonrigid matching requires us to automatically solve for correspondences between two sets of features
Results 1  10
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7,421