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

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

von Vladislav Golyanik

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Beschreibung

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

Target GroupsAbout the AuthorVladislav 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). 

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.

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 forcomputer vision and graphics (e.g., quantum computers and event cameras). 


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

Autor*in

Vladislav Golyanik

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

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

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Details

ISBN: 9783658305673
Verlag: Springer Fachmedien Wiesbaden GmbH
Erscheinung: 04.06.2020

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