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共 84 条记录，以下是61-70 订阅

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Defect classification on specular surfaces using wavelets

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4th international conference on scale space and variational methods in computer vision, ssvm 2013

作者： Hahn, Andreas Ziebarth, Mathias Heizmann, Michael Rieder, Andreas Karlsruhe Institute of Technology Institute for Applied and Numerical Mathematics Kaiserstr. 89-93 76133 Karlsruhe Germany Karlsruhe Institute of Technology Institute for Anthropomatics Adenauerring 4 76131 Karlsruhe Germany Fraunhofer Institute of Optronics System Technologies and Image Exploitation Fraunhoferstr. 1 76131 Karlsruhe Germany

ISBN: (纸本)9783642382666

In many practical problems wavelet theory offers methods to handle data in different scales. It is highly adaptable to represent data in a compact and sparse way without loss of information. We present an approach to find and classify defects on specular surfaces using pointwise extracted features in scale space. Our results confirm the presumption that the stationary wavelet transform is better suited to localize surface defects than the classical decimated transform. the classification is based on a support vector machine (SVM) and furthermore applicable to empirically evaluate given wavelets for specific classification tasks and can therefore be used as quality measure. © 2013 Springer-Verlag.

关键词： Wavelet transforms

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Solving the uncalibrated photometric stereo problem using total variation

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4th international conference on scale space and variational methods in computer vision, ssvm 2013

作者： Quéau, Yvain Lauze, François Durou, Jean-Denis IRIT UMR CNRS 5505 Toulouse France Dept. of Computer Science Univ. of Copenhagen Denmark

ISBN: (纸本)9783642382666

In this paper we propose a new method to solve the problem of uncalibrated photometric stereo, making very weak assumptions on the properties of the scene to be reconstructed. Our goal is to solve the generalized bas-relief ambiguity (GBR) by performing a total variation regularization of both the estimated normal field and albedo. Unlike most of the previous attempts to solve this ambiguity, our approach does not rely on any prior information about the shape or the albedo, apart from its piecewise smoothness. We test our method on real images and obtain results comparable to the state-of-the-art algorithms. © 2013 Springer-Verlag.

关键词： Photometry

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Layered mean shift methods

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4th international conference on scale space and variational methods in computer vision, ssvm 2013

作者： Šurkala, Milan Mozdřeň, Karel Fusek, Radovan Sojka, Eduard Technical University of Ostrava Faculty of Electrical Engieneering and Informatics 17. listopadu 15 708 33 Ostrava-Poruba Czech Republic

ISBN: (纸本)9783642382666

Segmentation is one of the most discussed problems in image processing. Many various methods for image segmentation exist. the mean-shift method is one of them and it was widely developed in recent years and it is still being developed. In this paper, we propose a new method called Layered Mean Shift that uses multiple mean-shift segmentations with different bandwidths stacked for elimination of the over-segmentation problem and finding the most appropriate segment boundaries. this method effectively reduces the need for the use of large kernels in the mean-shift method. therefore, it also significantly reduces the computational complexity. © 2013 Springer-Verlag.

关键词： Image segmentation

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Why is the census transform good for robust optic flow computation?

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4th international conference on scale space and variational methods in computer vision, ssvm 2013

作者： Hafner, David Demetz, Oliver Weickert, Joachim Mathematical Image Analysis Group Faculty of Mathematics and Computer Science Saarland University 66041 Saarbrücken Germany

ISBN: (纸本)9783642382666

the census transform is becoming increasingly popular in the context of optic flow computation in image sequences. Since it is invariant under monotonically increasing grey value transformations, it forms the basis of an illumination-robust constancy assumption. However, its underlying mathematical concepts have not been studied so far. the goal of our paper is to provide this missing theoretical foundation. We study the continuous limit of the inherently discrete census transform and embed it into a variational setting. Our analysis shows two surprising results: the census-based technique enforces matchings of extrema, and it induces an anisotropy in the data term by acting along level lines. Last but not least, we establish links to the widely-used gradient constancy assumption and present experiments that confirm our findings. © 2013 Springer-Verlag.

关键词： Anisotropy

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Partial optimality via iterative pruning for the potts model

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4th international conference on scale space and variational methods in computer vision, ssvm 2013

作者： Swoboda, Paul Savchynskyy, Bogdan Kappes, Jörg Schnörr, Christoph Image and Pattern Analysis Group University of Heidelberg Germany Heidelberg Collaboratory for Image Processing University of Heidelberg Germany

ISBN: (纸本)9783642382666

We propose a novel method to obtain a part of an optimal non-relaxed integral solution for energy minimization problems with Potts interactions, known also as the minimal partition problem. the method empirically outperforms previous approaches likeMQPBO and Kovtun's method in most of our test instances and especially in hard ones. As a starting point our approach uses the solution of a commonly accepted convex relaxation of the problem. this solution is then iteratively pruned until our criterion for partial optimality is satisfied. Due to its generality our method can employ any solver for the considered relaxed problem. © 2013 Springer-Verlag.

关键词： Iterative methods

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Compression of depth maps with segment-based homogeneous diffusion

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4th international conference on scale space and variational methods in computer vision, ssvm 2013

作者： Hoffmann, Sebastian Mainberger, Markus Weickert, Joachim Puhl, Michael Faculty of Mathematics and Computer Science Campus E1.7 Saarland University 66041 Saarbrücken Germany

ISBN: (纸本)9783642382666

the efficient compression of depth maps is becoming more and more important. We present a novel codec specifically suited for this task. In the encoding step we segment the image and extract between-pixel contours. Subsequently we optimise the grey values at carefully selected mask points, including both hexagonal grid locations as well as freely chosen points. We use a chain code to store the contours. For the decoding we apply a segment-based homogeneous diffusion inpainting. the segmentation allows parallel processing of the individual segments. Experiments show that our compression algorithm outperforms comparable methods such as JPEG or JPEG2000, while being competitive with HEVC (High Efficiency Video Coding). © 2013 Springer-Verlag.

关键词： Image compression

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Static and dynamic texture mixing using optimal transport

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4th international conference on scale space and variational methods in computer vision, ssvm 2013

作者： Ferradans, Sira Xia, Gui-Song Peyré, Gabriel Aujol, Jean-François Ceremade Univ. Paris-Dauphine France LIERSMARS Wuhan University China IMB Université Bordeaux 1 France

ISBN: (纸本)9783642382666

this paper tackles the problem of mixing static and dynamic texture by combining the statistical properties of an input set of images or videos. We focus on Spot Noise textures that follow a stationary and Gaussian model which can be learned from the given exemplars. From here, we define, using Optimal Transport, the distance between texture models, derive the geodesic path, and define the barycenter between several texture models. these derivations are useful because they allow the user to navigate inside the set of texture models, interpolating a new one at each element of the set. From these new interpolated models, new textures can be synthesized of arbitrary size in space and time. Numerical results obtained from a library of exemplars show the ability of our method to generate new complex and realistic static and dynamic textures. © 2013 Springer-Verlag.

关键词： Numerical methods

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variational method for computing average images of biological organs

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4th international conference on scale space and variational methods in computer vision, ssvm 2013

作者： Inagaki, Shun Imiya, Atsushi Hontani, Hidekata Hanaoka, Shouhei Masutani, Yoshitaka Graduate School of Advanced Integration Science Chiba University 1-33 Yayoi-cho Inage-ku Chiba 263-8522 Japan Institute of Media and Information Technology Chiba University 1-33 Yayoi-cho Inage-ku Chiba 263-8522 Japan Department of Computer Science Nagoya Institute of Technology Gokiso Showa-ku Nagoya Aichi 466-8555 Japan Department of Radiology University of Tokyo Hospital University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-8655 Japan

ISBN: (纸本)9783642382666

In this paper, we develop a variational method for the computation of average images of biological organs in three-dimensional Euclidean space. the average of three-dimensional biological organs is an essential feature to discriminate abnormal organs from normal organs. We combine the diffusion registration technique and optical flow computation for the computation of spatial deformation field between the averages and each input organ. We define the average as the shape which minimises the total deformation. © 2013 Springer-Verlag.

关键词： Biological organs

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Perspective photometric stereo with shadows

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4th international conference on scale space and variational methods in computer vision, ssvm 2013

作者： Mecca, Roberto Rosman, Guy Kimmel, Ron Bruckstein, Alfred M. Technion - Israel Institute of Technology Department of Computer Science Israel

ISBN: (纸本)9783642382666

High resolution reconstruction of 3D surfaces from images remains an active area of research since most of the methods in use are based on practical assumptions that limit their applicability. Furthermore, an additional complication in all active illumination 3D reconstruction methods is the presence of shadows, whose presence cause loss of information in the image data. We present an approach for the reconstruction of surfaces via Photometric Stereo, based on the perspective formulation of the Shape from Shading problem, solved via partial differential equations. Unlike many photometric stereo solvers that use computationally costly variational methods or a two-step approach, we use a novel, well-posed, differential formulation of the problem that enables us to solve a first order partial differential equation directly via an alternating directions raster scanning scheme. the resulting formulation enables surface computation for very large images and allows reconstruction in the presence of shadows. © 2013 Springer-Verlag.

关键词： Partial differential equations

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scale and edge detection with topological derivatives

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4th international conference on scale space and variational methods in computer vision, ssvm 2013

作者： Dong, Guozhi Grasmair, Markus Kang, Sung Ha Scherzer, Otmar Computational Science Center University of Vienna Nordbergstrasse 15 1090 Wien Austria Catholic University Eichstätt-Ingolstadt Ostenstrasse 26 85072 Eichstätt Germany School of Mathematics Georgia Institute of Technology 686 Cherry Street NW Atlanta GA 30332-0160 United States Austrian Academy of Sciences Altenbergerstrasse 69 A-4040 Linz Austria

ISBN: (纸本)9783642382666

A typical task of image segmentation is to partition a given image into regions of homogeneous property. In this paper we focus on the problem of further detecting scales of discontinuities of the image. the approach uses a recently developed iterative numerical algorithm for minimizing the Mumford-Shah functional which is based on topological derivatives. For the scale selection we use a squared norm of the gradient at edge points. During the iteration progress, the square norm, as a function varied with iteration numbers, provides information about different scales of the discontinuity sets. For realistic image data, the graph of the norm function is regularized by using total variation minimization to provide stable separation. We present the details of the algorithm and document various numerical experiments. © 2013 Springer-Verlag.

关键词： Edge detection

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