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检索条件"任意字段=4th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2013"

共 84 条记录，以下是41-50 订阅

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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 space and variational methods in computer vision 1

引用

丛书名： Lecture Notes in computer Science

1000年

作者： Luca Calatroni Marco Donatelli Serena Morigi Marco Prato Matteo Santacesaria

ISBN: (数字)9783031319754

ISBN: (纸本)9783031319747

this book constitutes the proceedings of the 9th international conference on scale space and variational methods in computer vision, ssvm 2023, which took place in Santa Margherita di Pula, Italy, in May 2023.;the 57 papers presented in this volume were carefully reviewed and selected from 72 submissions. they were organized in topical sections as follows: Inverse Problems in Imaging; Machine and Deep Learning in Imaging; Optimization for Imaging: theory and methods; scale space, PDEs, Flow, Motion and Registration.

关键词： Image Processing and computer vision computer Communication Networks computer Applications Machine Learning Mathematics of Computing Pattern Recognition

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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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Nonlinear Spectral Image Fusion 6th

Nonlinear Spectral Image Fusion

引用

6th international conference on scale space and variational methods in computer vision (ssvm)

作者： Benning, Martin Moeller, Michael Nossek, Raz Z. Burger, Martin Cremers, Daniel Gilboa, Guy Schonilibe, Carola-Bibiane Univ Cambridge Wilberforce Rd Cambridge CB3 0WA England Univ Siegen Holderlinstr 3 D-57076 Siegen Germany Technion IIT IL-32000 Haifa Israel Westfalische Wilhelms Univ Einsteinstr 62 D-48149 Munster Germany Tech Univ Munich Boltzmannstr 3 D-85748 Garching Germany

ISBN: (纸本)9783319587714;9783319587707

In this paper we demonstrate that the framework of non-linear spectral decompositions based on total variation (TV) regularization is very well suited for image fusion as well as more general image manipulation tasks. the well-localized and edge-preserving spectral TV decomposition allows to select frequencies of a certain image to transfer particular features, such as wrinkles in a face, from one image to another. We illustrate the effectiveness of the proposed approach in several numerical experiments, including a comparison to the competing techniques of Poisson image editing, linear osmosis, wavelet fusion and Laplacian pyramid fusion. We conclude that the proposed spectral TV image decomposition framework is a valuable tool for semi-and fully-automatic image editing and fusion.

关键词： Nonlinear spectral decomposition Total variation regularization Image fusion Image composition Multiscale methods

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Active contours for multi-region image segmentation with a single level set function

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

作者： Dubrovina, Anastasia Rosman, Guy Kimmel, Ron Computer Science Department Technion - IIT Haifa Israel

ISBN: (纸本)9783642382666

Segmenting the image into an arbitrary number of parts is at the core of image understanding. Many formulations of the task have been suggested over the years. Among these are axiomatic functionals, which are hard to implement and analyze, while graph-based alternatives impose a non-geometric metric on the problem. We propose a novel approach to tackle the problem of multiple-region segmentation for an arbitrary number of regions. the proposed framework allows generic region appearance models while avoiding metrication errors. Updating the segmentation in this framework is done by level set evolution. Yet, unlike most existing methods, evolution is executed using a single non-negative level set function, through the Voronoi Implicit Interface Method for a multi-phase interface evolution. We apply the proposed framework to synthetic and real images, with various number of regions, and compare it to state-of-the-art image segmentation algorithms. © 2013 Springer-Verlag.

关键词： Phase interfaces

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EmNeF: Neural Fields for Embedded variational Problems in Imaging 9th

EmNeF: Neural Fields for Embedded Variational Problems in ...

引用

9th international conference on scale space and variational methods in computer vision, ssvm 2023

作者： Bednarski, Danielle Lellmann, Jan Institute of Mathematics and Image Computing University of Lübeck Lübeck Germany

ISBN: (纸本)9783031319747

We propose a model-driven neural fields approach for solving variational problems. the approach can be applied to a variety of problems with convex, 1-homogeneous regularizer and arbitrary, possibly non-convex, data term. Our strategy is to embed the non-convex energy into a higher-dimensional space, reaching a convex primal-dual formulation. Instead of using classical gradient-descent based optimization algorithms, we propose training multiple fields representing the primal and dual variables in order to solve the problem. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Gradient methods

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Weighted patch-based reconstruction: Linking (multi-view) stereo to scale space

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

作者： Klowsky, Ronny Kuijper, Arjan Goesele, Michael Technische Universität Darmstadt Germany

ISBN: (纸本)9783642382666

Surface reconstruction using patch-based multi-view stereo commonly assumes that the underlying surface is locally planar. this is typically not true so that least-squares fitting of a planar patch leads to systematic errors which are of particular importance for multi-scale surface reconstruction. In a recent paper [12], we determined the modulation transfer function of a classical patch-based stereo system. Our key insight was that the reconstructed surface is a box-filtered version of the original surface. Since the box filter is not a true low-pass filter this causes high-frequency artifacts. In this paper, we propose an extended reconstruction model by weighting the least-squares fit of the 3D patch. We show that if the weighting function meets specified criteria the reconstructed surface is the convolution of the original surface with that weighting function. A choice of particular interest is the Gaussian which is commonly used in image and signal processing but left unexploited by many multi-view stereo algorithms. Finally, we demonstrate the effects of our theoretic findings using experiments on synthetic and real-world data sets. © 2013 Springer-Verlag.

关键词： Surface reconstruction

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