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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. Optical Flow, Motion Estimation and Registration

    1. Daniel Maurer, Michael Stoll, Andrés Bruhn
      Pages 550-562
    2. Jan Maas, Martin Rumpf, Stefan Simon
      Pages 563-577
    3. Abraham Marciano, Laurent D. Cohen, Najib Gadi
      Pages 578-589
    4. Kireeti Bodduna, Joachim Weickert
      Pages 590-601
    5. Robert Dalitz, Stefania Petra, Christoph Schnörr
      Pages 602-613
  2. 3D Vision

    1. Front Matter
      Pages 627-627
    2. Virginia Estellers, Stefano Soatto
      Pages 629-642
    3. Michiel H. J. Janssen, Tom C. J. Dela Haije, Frank C. Martin, Erik J. Bekkers, Remco Duits
      Pages 643-655
    4. Yvain Quéau, Tao Wu, Daniel Cremers
      Pages 656-668
    5. Robert Dachsel, Michael Breuß, Laurent Hoeltgen
      Pages 669-680
    6. Amit Boyarski, Alex M. Bronstein, Michael M. Bronstein
      Pages 681-693
    7. Jean Mélou, Yvain Quéau, Jean-Denis Durou, Fabien Castan, Daniel Cremers
      Pages 694-705
  3. Back Matter
    Pages 707-708

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
  • Buy this book on publisher's site
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