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

Format:

Book

Author/Creator:

Golyanik, Vladislav, author.

Contributor:

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

Language:

English

Subjects (All):

Optical data processing.

Artificial intelligence.

Machine learning.

Image Processing and Computer Vision.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Artificial Intelligence.

Machine Learning.

Local Subjects:

Image Processing and Computer Vision.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Artificial Intelligence.

Machine Learning.

Physical Description:

1 online resource (XXIV, 352 pages) : 119 illustrations, 13 illustrations in color

Edition:

First edition 2020.

Contained In:

Springer Nature eBook

Place of Publication:

Wiesbaden : Springer Fachmedien Wiesbaden : Imprint: Springer Vieweg, 2020.

System Details:

text file PDF

Summary:

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, id est 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). .

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.

Other Format:

Printed edition:

ISBN:

978-3-658-30567-3

9783658305673

Access Restriction:

Restricted for use by site license.