Scale Space and Variational Methods in Computer Vision (Paperback)

Jan Lellmann

ISBN 10: 3030223671 / ISBN 13: 9783030223670

Published by Springer Nature Switzerland AG, Cham, 2019

About this Item

Paperback. This book constitutes the proceedings of the 7th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2019, held in Hofgeismar, Germany, in June/July 2019. The 44 papers included in this volume were carefully reviewed and selected for inclusion in this book. They were organized in topical sections named: 3D vision and feature analysis; inpainting, interpolation and compression; inverse problems in imaging; optimization methods in imaging; PDEs and level-set methods; registration and reconstruction; scale-space methods; segmentation and labeling; and variational methods. This book constitutes the proceedings of the 7th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2019, held in Hofgeismar, Germany, in June/July 2019. optimization methods in imaging; PDEs and level-set methods; scale-space methods; and variational methods. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9783030223670

Bibliographic Details

• Title: Scale Space and Variational Methods in Computer Vision (Paperback)
• Publisher: Springer Nature Switzerland AG, Cham
• Publication Date: 2019
• Language: English
• ISBN 10: 3030223671
• ISBN 13: 9783030223670
• Binding: Paperback
• Condition: new

About this title

Synopsis

This book constitutes the proceedings of the 7th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2019, held in Hofgeismar, Germany, in June/July 2019. 

The 44 papers included in this volume were carefully reviewed and selected for inclusion in this book. They were organized in topical sections named: 3D vision and feature analysis; inpainting, interpolation and compression; inverse problems in imaging; optimization methods in imaging; PDEs and level-set methods; registration and reconstruction;  scale-space methods; segmentation and labeling; and variational methods.