Wide Area 2D/3D Imaging

Benjamin Langmann

ISBN 10: 3658064560 / ISBN 13: 9783658064563

Published by Springer Fachmedien Wiesbaden Jul 2014, 2014

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware -Imaging technology is an important research area and it is widely utilized in a growing number of disciplines ranging from gaming, robotics and automation to medicine. In the last decade 3D imaging became popular mainly driven by the introduction of novel 3D cameras and measuring devices. These cameras are usually limited to indoor scenes with relatively low distances. Benjamin Langmann introduces medium and long-range 2D/3D cameras to overcome these limitations. He reports measurement results for these devices and studies their characteristic behavior. In order to facilitate the application of these cameras, common algorithms are adapted to the 2D/3D data and new approaches for standard computer vision tasks are introduced. 152 pp. Englisch.

Seller Inventory # 9783658064563

Bibliographic Details

• Title: Wide Area 2D/3D Imaging
• Publisher: Springer Fachmedien Wiesbaden Jul 2014
• Publication Date: 2014
• Language: English
• ISBN 10: 3658064560
• ISBN 13: 9783658064563
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 210W x 148H x 9D millimeters 210 millimeters width by 148 millimeters height by 9 millimeters depth
• Weight: 207 grams

About this title

Synopsis

Imaging technology is an important research area and it is widely utilized in a growing number of disciplines ranging from gaming, robotics and automation to medicine. In the last decade 3D imaging became popular mainly driven by the introduction of novel 3D cameras and measuring devices. These cameras are usually limited to indoor scenes with relatively low distances. Benjamin Langmann introduces medium and long-range 2D/3D cameras to overcome these limitations. He reports measurement results for these devices and studies their characteristic behavior. In order to facilitate the application of these cameras, common algorithms are adapted to the 2D/3D data and new approaches for standard computer vision tasks are introduced.

About the Author

Benjamin Langmann studied computer science and mathematics at the Technical University of Braunschweig, received a doctorate degree from the University of Siegen and leads now the research group “Industrial and Medical Imaging” at the Institute for Measurement and Automatic Control of the Leibniz University Hannover, Germany.