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Robust Methods for Dense Monocular Non-Rigid 3D Reconstruction and Alignment of Point Clouds

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  • Computer vision primer: state-of-the-art methods

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  • ISBN: 978-3-658-30567-3
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Table of contents (11 chapters)

  1. Front Matter

    Pages I-XXIV
  2. Introduction

    • Vladislav Golyanik
    Pages 1-11
  3. Preliminaries

    • Vladislav Golyanik
    Pages 13-42
  4. Review of Previous Work

    • Vladislav Golyanik
    Pages 43-56
  5. Scalable Dense Non-Rigid Structure from Motion

    • Vladislav Golyanik
    Pages 57-88
  6. Summary, Conclusions and Outlook

    • Vladislav Golyanik
    Pages 313-315
  7. Back Matter

    Pages 317-352

About this book

Vladislav Golyanik proposes several new methods for dense non-rigid structure from motion (NRSfM) as well as alignment of point clouds. The introduced methods improve the state of the art in various aspects, i.e. in the ability to handle inaccurate point tracks and 3D data with contaminations. NRSfM with shape priors obtained on-the-fly from several unoccluded frames of the sequence and the new gravitational class of methods for point set alignment represent the primary contributions of this book.

Contents
  • Scalable Dense Non-rigid Structure from Motion
  • Shape Priors in Dense Non-rigid Structure from Motion
  • Probabilistic Point Set Registration with Prior Correspondences
  • Point Set Registration Relying on Principles of Particle Dynamics
Target Groups
  • Scientists and students in the fields of computer vision and graphics, machine learning, applied mathematics as well as related fields
  • Practitioners in industrial research and development in these fields
About the Author
Vladislav Golyanik is currently a postdoctoral researcher at the Max Planck Institute for Informatics in Saarbrücken, Germany. The current focus of his research lies on 3D reconstruction and analysis of general deformable scenes, 3D reconstruction of human body and matching problems on point sets and graphs. He is interested in machine learning (both supervised and unsupervised), physics-based methods as well as new hardware and sensors for computer vision and graphics (e.g., quantum computers and event cameras). 

Keywords

  • Non-Rigid Structure from Motion
  • NRSfM
  • Scalable Monocular Surface Reconstruction
  • Shape Priors for Non-rigid Structure from Motion
  • Monocular Surface Regression Networks
  • Coherent Depth Fields
  • High Dimensional Space Model
  • NRSfM with the State Recurrence Constraint
  • Probabilistic Point Set Registration with Prior Matches
  • Extended Coherent Point Drift
  • Human Appearance Transfer
  • Gravitational Approach for Point Set Registration
  • Barnes–Hut Rigid Gravitational Approach
  • Monocular Scene Flow Estimation
  • RGB-D Based Scene Flow Estimation

Authors and Affiliations

  • Computer Graphics D4, Max Planck Institute for Informatics, Saarbruecken, Germany

    Vladislav Golyanik

About the author

Vladislav Golyanik is currently a postdoctoral researcher at the Max Planck Institute for Informatics in Saarbrücken, Germany. The current focus of his research lies on 3D reconstruction and analysis of general deformable scenes, 3D reconstruction of human body and matching problems on point sets and graphs. He is interested in machine learning (both supervised and unsupervised), physics-based methods as well as new hardware and sensors for computer vision and graphics (e.g., quantum computers and event cameras). 

Bibliographic Information

  • Book Title: Robust Methods for Dense Monocular Non-Rigid 3D Reconstruction and Alignment of Point Clouds

  • Authors: Vladislav Golyanik

  • DOI: https://doi.org/10.1007/978-3-658-30567-3

  • Publisher: Springer Vieweg Wiesbaden

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020

  • Softcover ISBN: 978-3-658-30566-6

  • eBook ISBN: 978-3-658-30567-3

  • Edition Number: 1

  • Number of Pages: XXIV, 352

  • Number of Illustrations: 106 b/w illustrations, 13 illustrations in colour

  • Topics: Computer Vision, Virtual and Augmented Reality, Artificial Intelligence, Machine Learning

Buying options

eBook
USD 84.99
Price excludes VAT (USA)
  • ISBN: 978-3-658-30567-3
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD 109.99
Price excludes VAT (USA)