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

Af: Vladislav Golyanik Engelsk Paperback

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

Af: Vladislav Golyanik Engelsk Paperback
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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 for computer vision and graphics (e.g., quantum computers and event cameras). 

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

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Produktdetaljer
Sprog: Engelsk
Sider: 352
ISBN-13: 9783658305666
Indbinding: Paperback
Udgave:
ISBN-10: 3658305665
Kategori: Machine learning
Udg. Dato: 5 jun 2020
Længde: 0mm
Bredde: 148mm
Højde: 210mm
Forlag: Springer Fachmedien Wiesbaden
Oplagsdato: 5 jun 2020
Forfatter(e): Vladislav Golyanik
Forfatter(e) Vladislav Golyanik

Kategori Machine learning

ISBN-13 9783658305666

Sprog Engelsk

Indbinding Paperback

Sider 352

Udgave

Længde 0mm

Bredde 148mm

Højde 210mm

Udg. Dato 5 jun 2020

Oplagsdato 5 jun 2020

Forlag Springer Fachmedien Wiesbaden