Scale Space and Variational Methods in Computer Vision

6th International Conference, SSVM 2017, Kolding, Denmark, June 4-8, 2017, Proceedings

  • François Lauze
  • Yiqiu Dong
  • Anders Bjorholm Dahl
Conference proceedings SSVM 2017

Part of the Lecture Notes in Computer Science book series (LNCS, volume 10302)

Also part of the Image Processing, Computer Vision, Pattern Recognition, and Graphics book sub series (LNIP, volume 10302)

Table of contents

  1. Front Matter
    Pages I-XV
  2. Scale Space and PDE Methods

    1. Front Matter
      Pages 1-1
    2. Martin Benning, Michael Möller, Raz Z. Nossek, Martin Burger, Daniel Cremers, Guy Gilboa et al.
      Pages 41-53
    3. Fang Yang, Laurent D. Cohen
      Pages 54-65
    4. Laurent Hoeltgen, Isaac Harris, Michael Breuß, Andreas Kleefeld
      Pages 66-79
    5. Leonie Zeune, Stephan A. van Gils, Leon W. M. M. Terstappen, Christoph Brune
      Pages 80-93
  3. Restoration and Reconstruction

    1. Front Matter
      Pages 107-107
    2. Leah Bar, Nir Sochen, Nahum Kiryati
      Pages 109-120
    3. Robin Dirk Adam, Pascal Peter, Joachim Weickert
      Pages 121-132
    4. Jorge Gutierrez, Julien Rabin, Bruno Galerne, Thomas Hurtut
      Pages 172-183
    5. Paul Riot, Andrés Almansa, Yann Gousseau, Florence Tupin
      Pages 184-195
    6. Alasdair Newson, Noura Faraj, Julie Delon, Bruno Galerne
      Pages 196-207

About these proceedings

Introduction

This book constitutes the refereed proceedings of the 6th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2017, held in Kolding, Denmark, in June 2017. 
The 55 revised full papers presented were carefully reviewed and selected from 77 submissions. The papers are organized in the following topical sections: Scale Space and PDE Methods; Restoration and Reconstruction; Tomographic Reconstruction; Segmentation; Convex and Non-Convex Modeling and Optimization in Imaging; Optical Flow, Motion Estimation and Registration; 3D Vision.

Keywords

Image analysis Computer vision PDE Scale space Variational methods Optimization Segmentation Tomography Registration Optical flow 3D vision

Editors and affiliations

  1. 1.University of Copenhagen CopenhagenDenmark
  2. 2.Technical University of Denmark Kongens LyngbyDenmark
  3. 3.Technical University of Denmark Kongens LyngbyDenmark

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-58771-4
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-58770-7
  • Online ISBN 978-3-319-58771-4
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book