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Energy Minimization Methods in Computer Vision and Pattern Recognition

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

  • Marcello Pelillo
  • Edwin Hancock
Conference proceedings EMMCVPR 2017

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

Also part of the Image Processing, Computer Vision, Pattern Recognition, and Graphics book sub series (LNIP, volume 10746)

Table of contents

  1. Front Matter
    Pages I-XII
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  2. Clustering and Quantum Methods

    1. Front Matter
      Pages 1-1
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    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
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    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
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    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
    7. Optimizing Wavelet Bases for Sparser Representations
      Thomas Grandits, Thomas Pock
      Pages 249-262
    8. Bottom-Up Top-Down Cues for Weakly-Supervised Semantic Segmentation
      Qibin Hou, Daniela Massiceti, Puneet Kumar Dokania, Yunchao Wei, Ming-Ming Cheng, Philip H. S. Torr
      Pages 263-277
    9. Vehicle X-Ray Images Registration
      Abraham Marciano, Laurent D. Cohen, Najib Gadi
      Pages 278-293

  5. Colour, Shading and Reflectance of Light

    1. Front Matter
      Pages 295-295
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    2. Superpixels Optimized by Color and Shape
      Vitaliy Kurlin, Donald Harvey
      Pages 297-311
    3. Maximum Consensus Parameter Estimation by Reweighted \(\ell _1\) Methods
      Pulak Purkait, Christopher Zach, Anders Eriksson
      Pages 312-327
    4. A Graph Theoretic Approach for Shape from Shading
      Robert Scheffler, Ashkan Mansouri Yarahmadi, Michael Breuß, Ekkehard Köhler
      Pages 328-341
    5. A Variational Approach to Shape-from-Shading Under Natural Illumination
      Yvain Quéau, Jean Mélou, Fabien Castan, Daniel Cremers, Jean-Denis Durou
      Pages 342-357
    6. Sharpening Hyperspectral Images Using Spatial and Spectral Priors in a Plug-and-Play Algorithm
      Afonso M. Teodoro, José M. Bioucas-Dias, Mário A. T. Figueiredo
      Pages 358-371
    7. Inverse Lightfield Rendering for Shape, Reflection and Natural Illumination
      Antonin Sulc, Ole Johannsen, Bastian Goldluecke
      Pages 372-388
    8. Shadow and Specularity Priors for Intrinsic Light Field Decomposition
      Anna Alperovich, Ole Johannsen, Michael Strecke, Bastian Goldluecke
      Pages 389-406

  6. Propagation and Time-Evolution

    1. Front Matter
      Pages 407-407
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    2. Modelling Stable Backward Diffusion and Repulsive Swarms with Convex Energies and Range Constraints
      Leif Bergerhoff, Marcelo Cardénas, Joachim Weickert, Martin Welk
      Pages 409-423
    3. Euler-Lagrange Network Dynamics
      Jianjia Wang, Richard C. Wilson, Edwin R. Hancock
      Pages 424-438
    4. Slack and Margin Rescaling as Convex Extensions of Supermodular Functions
      Matthew B. Blaschko
      Pages 439-454
    5. Multi-object Convexity Shape Prior for Segmentation
      Lena Gorelick, Olga Veksler
      Pages 455-468
    6. Fast Asymmetric Fronts Propagation for Voronoi Region Partitioning and Image Segmentation
      Da Chen, Laurent D. Cohen
      Pages 469-484
    7. PointFlow: A Model for Automatically Tracing Object Boundaries and Inferring Illusory Contours
      Fang Yang, Alfred M. Bruckstein, Laurent D. Cohen
      Pages 485-498
    8. An Isotropic Minimal Path Based Framework for Segmentation and Quantification of Vascular Networks
      Emmanuel Cohen, Laurent D. Cohen, Thomas Deffieux, Mickael Tanter
      Pages 499-513

  7. Inference, Labeling and Relaxation

    1. Front Matter
      Pages 515-515
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    2. Limited-Memory Belief Propagation via Nested Optimization
      Christopher Zach
      Pages 517-532
    3. Geometric Image Labeling with Global Convex Labeling Constraints
      Artjom Zern, Karl Rohr, Christoph Schnörr
      Pages 533-547
    4. Discretized Convex Relaxations for the Piecewise Smooth Mumford-Shah Model
      Christopher Zach, Christian Häne
      Pages 548-563
    5. A Projected Gradient Descent Method for CRF Inference Allowing End-to-End Training of Arbitrary Pairwise Potentials
      Måns Larsson, Anurag Arnab, Fredrik Kahl, Shuai Zheng, Philip Torr
      Pages 564-579
  8. Back Matter
    Pages 581-582
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About these proceedings

Introduction

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.

Keywords

artificial intelligence clustering clustering analysis computer vision estimation image analysis image coding image processing image reconstruction machine learning motion estimation neural networks numerical methods object recognition optical flows optimization pattern recognition signal processing

Editors and affiliations

  1. 1.Ca’ Foscari University of VeniceVeniceItaly
  2. 2.University of YorkYorkUnited Kingdom

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-78199-0
  • Copyright Information Springer International Publishing AG, part of Springer Nature 2018
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science Computer Science (R0)
  • Print ISBN 978-3-319-78198-3
  • Online ISBN 978-3-319-78199-0
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site