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RGB-D Image Analysis and Processing

  • Book
  • © 2019

Overview

  • 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)

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Table of contents (18 chapters)

  1. RGB-D Data Acquisition and Processing

  2. RGB-D Data Analysis

  3. RGB-D Applications

Keywords

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

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