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  • 1.
    Gårding, Jonas
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Lindeberg, Tony
    KTH, Tidigare Institutioner, Numerisk analys och datalogi, NADA.
    Direct computation of shape cues using scale-adapted spatial derivative operators1996Inngår i: International Journal of Computer Vision, ISSN 0920-5691, E-ISSN 1573-1405, Vol. 17, nr 2, s. 163-191Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper addresses the problem of computing cues to the three-dimensional 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 scale-space, 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 multi-scale 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 an integration scale parameter determining over how large a region in space the statistics of regional descriptors is accumulated.Experimental results for both synthetic and natural images are presented, and the relation with models of biological vision is briefly discussed.

  • 2.
    Gårding, Jonas
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Lindeberg, Tony
    KTH, Tidigare Institutioner, Numerisk analys och datalogi, NADA.
    Direct estimation of local surface shape in a fixating binocular vision system1994Inngår i: Computer Vision — ECCV '94: Third European Conference on Computer Vision Stockholm, Sweden, May 2–6, 1994 Proceedings, Volume I, Springer Berlin/Heidelberg, 1994, s. 365-376Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This paper addresses the problem of computing cues to the three-dimensional structure of surfaces in the world directly from the local structure of the brightness pattern of a binocular image pair. The geometric information content of the gradient of binocular disparity is analyzed for the general case of a fixating vision system with symmetric or asymmetric vergence, and with either known or unknown viewing geometry. A computationally inexpensive technique which exploits this analysis is proposed. This technique allows a local estimate of surface orientation to be computed directly from the local statistics of the left and right image brightness gradients, without iterations or search. The viability of the approach is demonstrated with experimental results for both synthetic and natural gray-level images.

  • 3.
    Lindeberg, Tony
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
    Gårding, Jonas
    Shape from Texture from a Multi-Scale Perspective1993Inngår i: Fourth International Conference on Computer Vision, 1993. Proceedings: ICCV'93 / [ed] H.-H. Nagel, IEEE conference proceedings, 1993, s. 683-691Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The problem of scale in shape from texture is addressed. The need for (at least) two scale parameters is emphasized; a local scale describing the amount of smoothing used for suppressing noise and irrelevant details when computing primitive texture descriptors from image data, and an integration scale describing the size of the region in space over which the statistics of the local descriptors is accumulated.

    A novel mechanism for automatic scale selection is used, based on normalized derivatives. It is used for adaptive determination of the two scale parameters in a multi-scale texture descriptor, thewindowed second moment matrix, which is defined in terms of Gaussian smoothing, first order derivatives, and non-linear pointwise combinations of these. The same scale-selection method can be used for multi-scale blob detection without any tuning parameters or thresholding.

    The resulting texture description can be combined with various assumptions about surface texture in order to estimate local surface orientation. Two specific assumptions, ``weak isotropy'' and ``constant area'', are explored in more detail. Experiments on real and synthetic reference data with known geometry demonstrate the viability of the approach.

  • 4.
    Lindeberg, Tony
    et al.
    KTH, Tidigare Institutioner, Numerisk analys och datalogi, NADA.
    Gårding, Jonas
    Shape-adapted smoothing in estimation of 3-D depth cues from affine distortions of local 2-D brightness structure1997Inngår i: Image and Vision Computing, ISSN 0262-8856, E-ISSN 1872-8138, Vol. 15, nr 6, s. 415-434Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This article describes a method for reducing the shape distortions due to scale-space smoothing that arise in the computation of 3-D shape cues using operators (derivatives) defined from scale-space representation. More precisely, we are concerned with a general class of methods for deriving 3-D shape cues from a 2-D image data based on the estimation of locally linearized deformations of brightness patterns. This class constitutes a common framework for describing several problems in computer vision (such as shape-from-texture, shape-from disparity-gradients, and motion estimation) and for expressing different algorithms in terms of similar types of visual front-end-operations. It is explained how surface orientation estimates will be biased due to the use of rotationally symmetric smoothing in the image domain. These effects can be reduced by extending the linear scale-space concept into an affine Gaussian scalespace representation and by performing affine shape adaptation of the smoothing kernels. This improves the accuracy of the surface orientation estimates, since the image descriptors, on which the methods are based, will be relative invariant under affine transformations, and the error thus confined to the higher-order terms in the locally linearized perspective transformation. A straightforward algorithm is presented for performing shape adaptation in practice. Experiments on real and synthetic images with known orientation demonstrate that in the presence of moderately high noise levels the accuracy is improved by typically one order of magnitude.

  • 5.
    Lindeberg, Tony
    et al.
    KTH, Tidigare Institutioner, Numerisk analys och datalogi, NADA.
    Gårding, Jonas
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Shape-Adapted Smoothing in Estimation of 3-D Depth Cues from Affine Distortions of Local 2-D Brightness Structure1994Inngår i: Computer Vision — ECCV '94: Third European Conference on Computer Vision Stockholm, Sweden, May 2–6, 1994 Proceedings, Volume I, 1994, s. 389-400Konferansepaper (Fagfellevurdert)
    Abstract [en]

    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 3-D shape cues from 2-D image data, which are based on the estimation of locally linearized distortion of brightness patterns. By extending the linear scale-space concept into an affine scale-spacerepresentation 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 affine transformations, and the error will thus be confined to the higher-order terms in the locally linearized perspective mapping.

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