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Detecting Salient BlobLike Image Structures with a ScaleSpace Primal Sketch: A Method for FocusofAttention
 INT. J. COMP. VISION
, 1993
"... This article presents: (i) a multiscale representation of greylevel shape called the scalespace primal sketch, which makes explicit both features in scalespace and the relations between structures at different scales, (ii) a methodology for extracting significant bloblike image structures from ..."
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Cited by 157 (13 self)
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This article presents: (i) a multiscale representation of greylevel shape called the scalespace primal sketch, which makes explicit both features in scalespace and the relations between structures at different scales, (ii) a methodology for extracting significant bloblike image structures from this representations, and (iii) applications to edge detection, histogram analysis, and junction classification demonstrating how the proposed method can be used for guiding later stage visual processes. The representation gives a qualitative description of image structure, which allows for detection of stable scales and associated regions of interest in a solely bottomup datadriven way. In other words, it generates coarse segmentation cues, and can hence be seen as preceding further processing, which can then be properly tuned. It is argued that once such information is available, many other processing tasks can become much simpler. Experiments on real imagery demonstrate that the proposed theory gives intuitive results.
Shapeadapted smoothing in estimation of 3D depth cues from affine distortions of local 2D brightness structure
 IN PROC. 3RD EUROPEAN CONF. ON COMPUTER VISION
, 1994
"... Rotationally symmetric operations in the image domain may give rise to shape distortions. This article describes a way of reducing this effect for a general class of methods for deriving 3D shape cues from 2D image data, which are based on the estimation of locally linearized distortion of brightn ..."
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Cited by 71 (15 self)
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Rotationally symmetric operations in the image domain may give rise to shape distortions. This article describes a way of reducing this effect for a general class of methods for deriving 3D shape cues from 2D image data, which are based on the estimation of locally linearized distortion of brightness patterns. By extending the linear scalespace concept into an affine scalespace representation and performing affine shape adaption of the smoothing kernels, the accuracy of surface orientation estimates derived from texture and disparity cues can be improved by typically one order of magnitude. The reason for this is that the image descriptors, on which the methods are based, will be relative invariant under a ne transformations, and the error will thus be confined to the higherorder terms in the locally linearized perspective mapping.
Direct Computation of Shape Cues Using ScaleAdapted Spatial Derivative Operators
 International Journal of Computer Vision
, 1996
"... This paper addresses the problem of computing cues to the threedimensional structure of surfaces in the world directly from the local structure of the brightness pattern of either a single monocular image or a binocular image pair. It is shown that starting from Gaussian derivatives of order up to ..."
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Cited by 59 (9 self)
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This paper addresses the problem of computing cues to the threedimensional structure of surfaces in the world directly from the local structure of the brightness pattern of either a single monocular image or a binocular image pair. It is shown that starting from Gaussian derivatives of order up to two at a range of scales in scalespace, local estimates of (i) surface orientation from monocular texture foreshortening, (ii) surface orientation from monocular texture gradients, and (iii) surface orientation from the binocular disparity gradient can be computed without iteration or search, and by using essentially the same basic mechanism. The methodology is based on a multiscale descriptor of image structure called the windowed second moment matrix, which is computed with adaptive selection of both scale levels and spatial positions. Notably, this descriptor comprises two scale parameters; a local scale parameter describing the amount of smoothing used in derivative computations, and a...
Shapeadapted smoothing in estimation of 3D shape cues from affine distortions of local 2D brightness structure
, 2001
"... This article describes a method for reducing the shape distortions due to scalespace smoothing that arise in the computation of 3D shape cues using operators (derivatives) de ned from scalespace representation. More precisely, we are concerned with a general class of methods for deriving 3D shap ..."
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Cited by 56 (3 self)
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This article describes a method for reducing the shape distortions due to scalespace smoothing that arise in the computation of 3D shape cues using operators (derivatives) de ned from scalespace representation. More precisely, we are concerned with a general class of methods for deriving 3D shape cues from 2D image data based on the estimation of locally linearized deformations of brightness patterns. This class
Shape From Texture for Smooth Curved Surfaces in Perspective Projection
 Journal of Mathematical Imaging and Vision
, 1992
"... Projective distortion of surface texture observed in a perspective image can provide direct information about the shape of the underlying surface. Previous theories have generally concerned planar surfaces; in this paper we present a systematic analysis of first and secondorder texture distortion ..."
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Cited by 52 (6 self)
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Projective distortion of surface texture observed in a perspective image can provide direct information about the shape of the underlying surface. Previous theories have generally concerned planar surfaces; in this paper we present a systematic analysis of first and secondorder texture distortion cues for the case of a smooth curved surface. In particular, we analyze several kinds of texture gradients and relate them to surface orientation and surface curvature. The local estimates obtained from these cues can be integrated to obtain a global surface shape, and we show that the two surfaces resulting from the wellknown tilt ambiguity in the local foreshortening cue typically have qualitatively different shapes. As an example of a practical application of the analysis, a shape from texture algorithm based on local orientationselective filtering is described, and some experimental results are shown. i Figure 1: This image of a slanting plane covered with circles illustrates several...
On scale selection for differential operators
 8TH SCIA
, 1993
"... Although traditional scalespace theory provides a wellfounded framework for dealing with image structures at different scales, it does not directly address the problem of how to select appropriate scales for further analysis. This paper introduces a new tool for dealing with this problem. A heur ..."
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Cited by 50 (10 self)
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Although traditional scalespace theory provides a wellfounded framework for dealing with image structures at different scales, it does not directly address the problem of how to select appropriate scales for further analysis. This paper introduces a new tool for dealing with this problem. A heuristic principle is proposed stating that local extrema over scales of different combinations of normalized scale invariant derivatives are likely candidates to correspond to interesting structures. Support is given by theoretical considerations and experiments on real and synthetic data. The resulting methodology lends itself naturally to twostage algorithms; feature detection at coarse scales followed by feature localization at ner scales. Experiments on blob detection, junction detection and edge detection demonstrate that the proposed method gives intuitively reasonable results.
Shape from texture from a multiscale perspective
 In Proc. 4th International Conference on Computer Vision
, 1993
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Principles for automatic scale selection
 Handbook on Computer Vision and Applications
, 1999
"... 1Abstract: An inherent property of objects in the world is that they only exist as meaningful entities over certain ranges of scale. If one aims at describing the structure of unknown realworld signals, then a multiscale representation of data is of crucial importance. Whereas conventional scales ..."
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Cited by 28 (1 self)
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1Abstract: An inherent property of objects in the world is that they only exist as meaningful entities over certain ranges of scale. If one aims at describing the structure of unknown realworld signals, then a multiscale representation of data is of crucial importance. Whereas conventional scalespace theory provides a wellfounded framework for dealing with image structures at dierent scales, this theory does not directly address the problem of how to select appropriate scales for further analysis. This chapter outlines a systematic methodology of how mechanisms for automatic scale selection can be formulated in the problem domains of feature detection and image matching (
ow estimation), respectively. For feature detectors expressed in terms of Gaussian derivatives, hypotheses about interesting scale levels can be generated from scales at which normalized measures of feature strength assume local maxima with respect to scale. It is shown how the notion of normalized derivatives arises by necessity given the requirement that the scale selection mechanism should
3D Computer Vision Using Structured Light: Design, Calibration and Implementation Issues
 Design, Calibration, and Implementation Issues,” Advances in Computers(43
, 1996
"... Structured Light (SL) sensing is a well established method of range acquisition for Computer Vision. This chapter provides thorough discussions of design issues, calibration methodologies and implementation schemes for SL sensors. The challenges for SL sensor development are described and a range of ..."
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Cited by 26 (2 self)
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Structured Light (SL) sensing is a well established method of range acquisition for Computer Vision. This chapter provides thorough discussions of design issues, calibration methodologies and implementation schemes for SL sensors. The challenges for SL sensor development are described and a range of approaches are surveyed. A novel SL sensor, PRIME, the PRofile Imaging ModulE has recently been developed and is used as a design example in the detailed discussions. KEYWORDS: Computer Vision,Range Image Acquisition, Structured Light Ranging, RealTime Machine Vision, Sensor Calibration 0y This research is sponsored in part by grants awarded by the Japan Railways and the Office of Technology Development, U.S. Department of Energy. 1 Introduction Machine vision as a discipline and technology owes its creation, development and growth to digital computers. Without computers machine vision is not possible. The main objective of machine vision is to extract information useful for performin...
Surface orientation and curvature from differential texture distortion
, 1995
"... A unified differential geometric framework for estimation of local surface shapeand orientation from projective texture distortion is proposed, based on a differential version of the texture stationarity assumption introduced by Malik and Rosenholtz. This framework allows the information content of ..."
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Cited by 26 (0 self)
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A unified differential geometric framework for estimation of local surface shapeand orientation from projective texture distortion is proposed, based on a differential version of the texture stationarity assumption introduced by Malik and Rosenholtz. This framework allows the information content of the gradient of any texture descriptor defined inalocal coordinate frametobe characterized in a very compact form. The analysis encompasses both full a ne texture descriptors and the classical "texture gradients". For estimation of local surface orientation and curvature from uncertain observations of affine texture distortion, the proposed framework allows the dimensionality of the search space tobereduced from five to one.