Energy Minimization Methods in Computer Vision and Pattern Recognition

10th International Conference, EMMCVPR 2015, Hong Kong, China, January 13-16, 2015. Proceedings

  • Xue-Cheng Tai
  • Egil Bae
  • Tony F. Chan
  • Marius Lysaker
Conference proceedings EMMCVPR 2015

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8932)

Table of contents

  1. Front Matter
  2. Discrete and Continuous Optimization

    1. Viktor Larsson, Carl Olsson
      Pages 1-14
    2. Hossein Mobahi, John W. Fisher III
      Pages 43-56
    3. Hossein Mobahi, John W. Fisher III
      Pages 71-84
  3. Image Restoration and Inpainting

    1. Jeremias Sulam, Michael Elad
      Pages 99-111
    2. Daniele Perrone, Remo Diethelm, Paolo Favaro
      Pages 112-125
    3. Thomas Möllenhoff, Evgeny Strekalovskiy, Michael Moeller, Daniel Cremers
      Pages 126-140
    4. Joan Duran, Michael Moeller, Catalina Sbert, Daniel Cremers
      Pages 141-154
    5. Ronny Bergmann, Andreas Weinmann
      Pages 155-168
    6. Sebastian Hoffmann, Gerlind Plonka, Joachim Weickert
      Pages 169-182
  4. Segmentation

    1. Konstantin Dragomiretskiy, Dominique Zosso
      Pages 197-208
    2. Huiyi Hu, Justin Sunu, Andrea L. Bertozzi
      Pages 209-222
    3. Aditya Tatu, Sumukh Bansal
      Pages 223-236
    4. Xingping Dong, Jianbing Shen, Luc Van Gool
      Pages 237-248
    5. Kunqian Li, Wenbing Tao, Xiangli Liao, Liman Liu
      Pages 249-262

About these proceedings

Introduction

This volume constitutes the refereed proceedings of the 10th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2015, held in Hong Kong, China, in January 2015. The 36 revised full papers were carefully reviewed and selected from 45 submissions. The papers are organized in topical sections on discrete and continuous optimization; image restoration and inpainting; segmentation; PDE and variational methods; motion, tracking and multiview reconstruction; statistical methods and learning; and medical image analysis.

Keywords

clustering algorithm computer vision convex optimization image processing iterative methods machine learning multi-view stereo numerical analysis optic disk optimization pattern recognition semantic image segmentation statistical methods total variation variational methods

Editors and affiliations

  • Xue-Cheng Tai
    • 1
  • Egil Bae
    • 2
  • Tony F. Chan
    • 3
  • Marius Lysaker
    • 4
  1. 1.Department of MathematicsUniversity of BergenBergenNorway
  2. 2.Department of MathematicsUniversity of CaliforniaLos AngelesUSA
  3. 3.The Hong Kong University of Science and TechnologyKowloonHong Kong, S.A.R.
  4. 4.Telemark University CollegePorsgrunnNorway

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-14612-6
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-14611-9
  • Online ISBN 978-3-319-14612-6
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book
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