RGB-D image analysis and processing / Paul L. Rosin, Yu-Kun Lai, Ling Shao, Yonghuai Liu, editors.
Rosin, Paul L., editor.; Lai, Yu-Kun, editor.; Shao, Ling, Dr., editor.; Liu, Yonghuai, editor.
2019
TA1637 .R43 2019eb
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Title RGB-D image analysis and processing / Paul L. Rosin, Yu-Kun Lai, Ling Shao, Yonghuai Liu, editors.
ISBN 9783030286033 (electronic book)
3030286037 (electronic book)
9783030286026
DOI https://doi.org/10.1007/978-3-030-28603-3
https://doi.org/10.1007/978-3-030-28
Published Cham : Springer, [2019]
Copyright ©2019
Language English
Description 1 online resource : illustrations.
Item Number 10.1007/978-3-030-28603-3 doi
10.1007/978-3-030-28
Call Number TA1637 .R43 2019eb
Dewey Decimal Classification 621.36/7
Summary 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.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed October 31, 2019).
Added Author Rosin, Paul L., editor.
Lai, Yu-Kun, editor.
Shao, Ling, Dr., editor.
Liu, Yonghuai, editor.
Series Advances in computer vision and pattern recognition.
Available in Other Form RGB-D Image Analysis and Processing
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
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Part I RGB-D Data Acquisition and Processing
RGB-D Sensors: Data Acquisition
Dealing with Missing Depth: Recent Advances in Depth Image Completion and Estimation
Depth Super-resolution With Color Guidance: A Review
RGB-D Sensors Data Quality Assessment and Improvement for Advanced Applications
3D Reconstruction from RGB-D Data
RGB-D Odometry and SLAM
Enhancing 3D Capture with Multiple Depth Camera Systems: A State-of-the-Art Report
Part II RGB-D Data Analysis
RGB-D Image-based Object Detection: from Traditional Methods to Deep Learning Techniques
RGB-S Salient Object Detection: A Review
Foreground Detection and segmentation in RGB-D Images
Instance- and Category-level 6d Object Pose Estimation
Part III RGB-D Applications
Semantic RGB-D Perception for Cognitive Service Robots
RGB-D Sensors and Signal Processing for Fall Detection
RGB-D Interactive Systems on Serious Games for Motor Rehabilitation Therapy and Therapeutic Measurements
Real-Time Hand Pose Estimation using Depth Camera.-RGB-D Object Classification for Autonomous Driving Perception
People Counting in Crowded Environment and Re-identification
References
Index.

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