Editors:
- Covers the full range of RGB-D imaging: RGB-D data acquisition and processing, RGB-D data analysis, RGB-D applications
- Detailed coverage of RGB-D imaging providing technical depth
- Each chapter is written by an expert/s specialising in the respective topic
- Includes dedicated chapters that cover a wide range of applications of RGB-D imaging of interest to both specialists and practitioners
- Extensively illustrated with visually attractive and informative examples of RGB-D imaging
Part of the book series: Advances in Computer Vision and Pattern Recognition (ACVPR)
Buy it now
Buying options
Tax calculation will be finalised at checkout
Other ways to access
This is a preview of subscription content, log in via an institution to check for access.
Table of contents (18 chapters)
-
Front Matter
-
RGB-D Data Acquisition and Processing
-
Front Matter
-
-
RGB-D Data Analysis
-
Front Matter
-
-
RGB-D Applications
-
Front Matter
-
About this book
This book focuses on the fundamentals and recent advances in RGB-D imaging as well as covering a range of RGB-D applications. The topics covered include: data acquisition, data quality assessment, filling holes, 3D reconstruction, SLAM, multiple depth camera systems, segmentation, object detection, salience detection, pose estimation, geometric modelling, fall detection, autonomous driving, motor rehabilitation therapy, people counting and cognitive service robots.
The availability of cheap RGB-D sensors has led to an explosion over the last five years in the capture and application of colour plus depth data. The addition of depth data to regular RGB images vastly increases the range of applications, and has resulted in a demand for robust and real-time processing of RGB-D data. There remain many technical challenges, and RGB-D image processing is an ongoing research area. This book covers the full state of the art, and consists of a series of chapters by internationally renowned experts in the field. Each chapter is written so as to provide a detailed overview of that topic. RGB-D Image Analysis and Processing will enable both students and professional developers alike to quickly get up to speed with contemporary techniques, and apply RGB-D imaging in their own projects.
Editors and Affiliations
-
School of Computer Science and Informatics, Cardiff University, Cardiff, UK
Paul L. Rosin, Yu-Kun Lai
-
IEEE, University of East Anglia, Norwich, UK
Ling Shao
-
Department of Computer Science, Edge Hill University, Ormskirk, UK
Yonghuai Liu
Bibliographic Information
Book Title: RGB-D Image Analysis and Processing
Editors: Paul L. Rosin, Yu-Kun Lai, Ling Shao, Yonghuai Liu
Series Title: Advances in Computer Vision and Pattern Recognition
DOI: https://doi.org/10.1007/978-3-030-28603-3
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Hardcover ISBN: 978-3-030-28602-6Published: 06 November 2019
Softcover ISBN: 978-3-030-28605-7Published: 06 November 2020
eBook ISBN: 978-3-030-28603-3Published: 26 October 2019
Series ISSN: 2191-6586
Series E-ISSN: 2191-6594
Edition Number: 1
Number of Pages: XI, 524
Number of Illustrations: 26 b/w illustrations, 152 illustrations in colour
Topics: Image Processing and Computer Vision, User Interfaces and Human Computer Interaction, Artificial Intelligence