Scale Space and Variational Methods in Computer Vision

1. Front Matter

   Pages i-xvii

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2. 3D Vision and Feature Analysis

   1. Front Matter

      Pages 1-1

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   2. The Fractional Harris-Laplace Feature Detector

      • Matthew Adams

      Pages 3-12

   3. Macrocanonical Models for Texture Synthesis

      • Valentin De Bortoli, Agnès Desolneux, Bruno Galerne, Arthur Leclaire

      Pages 13-24

   4. Finding Structure in Point Cloud Data with the Robust Isoperimetric Loss

      • Shay Deutsch, Iacopo Masi, Stefano Soatto

      Pages 25-37

   5. Deep Eikonal Solvers

      • Moshe Lichtenstein, Gautam Pai, Ron Kimmel

      Pages 38-50

   6. A Splitting-Based Algorithm for Multi-view Stereopsis of Textureless Objects

      • Jean Mélou, Yvain Quéau, Fabien Castan, Jean-Denis Durou

      Pages 51-63

3. Inpainting, Interpolation and Compression

   1. Front Matter

      Pages 65-65

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   2. Pseudodifferential Inpainting: The Missing Link Between PDE- and RBF-Based Interpolation

      • Matthias Augustin, Joachim Weickert, Sarah Andris

      Pages 67-78

   3. Towards PDE-Based Video Compression with Optimal Masks and Optic Flow

      • Laurent Hoeltgen, Michael Breuß, Georg Radow

      Pages 79-91

   4. Compressing Audio Signals with Inpainting-Based Sparsification

      • Pascal Peter, Jan Contelly, Joachim Weickert

      Pages 92-103

   5. Alternate Structural-Textural Video Inpainting for Spot Defects Correction in Movies

      • Arthur Renaudeau, François Lauze, Fabien Pierre, Jean-François Aujol, Jean-Denis Durou

      Pages 104-116

4. Inverse Problems in Imaging

   1. Front Matter

      Pages 117-117

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   2. Iterative Sampled Methods for Massive and Separable Nonlinear Inverse Problems

      • Julianne Chung, Matthias Chung, J. Tanner Slagel

      Pages 119-130

   3. Refitting Solutions Promoted by \(\ell _{12}\) Sparse Analysis Regularizations with Block Penalties

      • Charles-Alban Deledalle, Nicolas Papadakis, Joseph Salmon, Samuel Vaiter

      Pages 131-143

   4. An Iteration Method for X-Ray CT Reconstruction from Variable-Truncation Projection Data

      • Limei Huo, Shousheng Luo, Yiqiu Dong, Xue-Cheng Tai, Yang Wang

      Pages 144-155

   5. A New Iterative Method for CT Reconstruction with Uncertain View Angles

      • Nicolai André Brogaard Riis, Yiqiu Dong

      Pages 156-167

5. Optimization Methods in Imaging

   1. Front Matter

      Pages 169-169

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   2. Time Discrete Geodesics in Deep Feature Spaces for Image Morphing

      • Alexander Effland, Erich Kobler, Thomas Pock, Martin Rumpf

      Pages 171-182

   3. Minimal Lipschitz Extensions for Vector-Valued Functions on Finite Graphs

      • Johannes Hertrich, Miroslav Bačák, Sebastian Neumayer, Gabriele Steidl

      Pages 183-195

This book constitutes the proceedings of the 7th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2019, held in Hofgeismar, Germany, in June/July 2019. The 44 papers included in this volume were carefully reviewed and selected for inclusion in this book. They were organized in topical sections named: 3D vision and feature analysis; inpainting, interpolation and compression; inverse problems in imaging; optimization methods in imaging; PDEs and level-set methods; registration and reconstruction;  scale-space methods; segmentation and labeling; and variational methods. 

• artificial intelligence
• computer vision
• estimation
• image coding
• image compression
• image processing
• image reconstruction
• image registration
• image segmentation
• inverse problems
• motion estimation
• neural networks
• numerical experiments
• numerical methods
• optical flows
• partial differential equations
• reconstruction
• regularization
• signal processing
• variational methods

• University of Lübeck, Lübeck, Germany

  Jan Lellmann, Jan Modersitzki

• University of Erlangen-Nuremberg (FAU), Erlangen, Germany

  Martin Burger

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