Skip to main content
SpringerLink
Log in
Book cover

Energy Minimization Methods in Computer Vision and Pattern Recognition

11th International Conference, EMMCVPR 2017, Venice, Italy, October 30 – November 1, 2017, Revised Selected Papers

  • Conference proceedings
  • © 2018

Overview

Editors:
  1. Marcello Pelillo

    1. Ca’ Foscari University of Venice, Venice, Italy

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  2. Edwin Hancock

    1. University of York, York, United Kingdom

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10746)

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

Included in the following conference series:

Conference proceedings info: EMMCVPR 2017.

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (37 papers)

  1. Front Matter

    Pages I-XII
    Download chapter PDF

  2. Clustering and Quantum Methods

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Ising Models for Binary Clustering via Adiabatic Quantum Computing

      • Christian Bauckhage, E. Brito, K. Cvejoski, C. Ojeda, Rafet Sifa, S. Wrobel
      Pages 3-17

    3. Quantum Interference and Shape Detection

      • Davi Geiger, Zvi M. Kedem
      Pages 18-33

    4. Structured Output Prediction and Learning for Deep Monocular 3D Human Pose Estimation

      • Stefan Kinauer, Riza Alp Güler, Siddhartha Chandra, Iasonas Kokkinos
      Pages 34-48

    5. Dominant Set Biclustering

      • Matteo Denitto, Manuele Bicego, Alessandro Farinelli, Marcello Pelillo
      Pages 49-61

    6. Bragg Diffraction Patterns as Graph Characteristics

      • Francisco Escolano, Edwin R. Hancock
      Pages 62-75

  3. Motion and Tracking

    1. Front Matter

      Pages 77-77
      Download chapter PDF

    2. Variational Large Displacement Optical Flow Without Feature Matches

      • Michael Stoll, Daniel Maurer, Andrés Bruhn
      Pages 79-92

    3. Temporal Semantic Motion Segmentation Using Spatio Temporal Optimization

      • Nazrul Haque, N. Dinesh Reddy, Madhava Krishna
      Pages 93-108

    4. Depth-Adaptive Computational Policies for Efficient Visual Tracking

      • Chris Ying, Katerina Fragkiadaki
      Pages 109-122

    5. Multiframe Motion Coupling for Video Super Resolution

      • Jonas Geiping, Hendrik Dirks, Daniel Cremers, Michael Moeller
      Pages 123-138

    6. Illumination-Aware Large Displacement Optical Flow

      • Michael Stoll, Daniel Maurer, Sebastian Volz, Andrés Bruhn
      Pages 139-154

    7. Location Uncertainty Principle: Toward the Definition of Parameter-Free Motion Estimators

      • Shengze Cai, Etienne Mémin, Pierre Dérian, Chao Xu
      Pages 155-171

  4. Image Processing and Segmentation

    1. Front Matter

      Pages 173-173
      Download chapter PDF

    2. Autonomous Multi-camera Tracking Using Distributed Quadratic Optimization

      • Yusuf Osmanlıoğlu, Bahareh Shakibajahromi, Ali Shokoufandeh
      Pages 175-188

    3. Nonlinear Compressed Sensing for Multi-emitter X-Ray Imaging

      • Maria Klodt, Raphael Hauser
      Pages 189-204

    4. Unified Functional Framework for Restoration of Image Sequences Degraded by Atmospheric Turbulence

      • Naftali Zon, Nahum Kiryati
      Pages 205-219

    5. A Convex Approach to K-Means Clustering and Image Segmentation

      • Laurent Condat
      Pages 220-234

    6. Luminance-Guided Chrominance Denoising with Debiased Coupled Total Variation

      • Fabien Pierre, Jean-François Aujol, Charles-Alban Deledalle, Nicolas Papadakis
      Pages 235-248
Back to top

Other volumes

  1. Energy Minimization Methods in Computer Vision and Pattern Recognition

Keywords

About this book

This volume constitutes the refereed proceedings of the 11th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2017, held in Venice, Italy, in October/November 2017.

The 37 revised full papers were carefully reviewed and selected from 51 submissions. The papers are organized in topical sections on Clustering and Quantum Methods; Motion and Tracking; Image Processing and Segmentation; Color, Shading and Reflectance of Light; Propagation and Time-evolution; and Inference, Labeling, and Relaxation.

Editors and Affiliations

  • Ca’ Foscari University of Venice, Venice, Italy

    Marcello Pelillo

  • University of York, York, United Kingdom

    Edwin Hancock

Bibliographic Information

Publish with us

Policies and ethics

Back to top

Search

Navigation