3D Imaging, Analysis and Applications / edited by Yonghuai Liu, Nick Pears, Paul L. Rosin, Patrik Huber.

Format:

Book

Contributor:

Liu, Yonghuai, editor.

Pears, Nick, editor.

Rosin, Paul L., editor.

Huber, Patrik, editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

Language:

English

Subjects (All):

Optical data processing.

Image Processing and Computer Vision.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Local Subjects:

Image Processing and Computer Vision.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Physical Description:

1 online resource (XII, 736 pages) : 266 illustrations, 220 illustrations in color

Edition:

Second edition 2020.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2020.

System Details:

text file PDF

Summary:

This textbook is designed for postgraduate studies in the field of 3D Computer Vision. It also provides a useful reference for industrial practitioners; for example, in the areas of 3D data capture, computer-aided geometric modelling and industrial quality assurance. This second edition is a significant upgrade of existing topics with novel findings. Additionally, it has new material covering consumer-grade RGB-D cameras, 3D morphable models, deep learning on 3D datasets, as well as new applications in the 3D digitization of cultural heritage and the 3D phenotyping of crops. Overall, the book covers three main areas: ● 3D imaging, including passive 3D imaging, active triangulation 3D imaging, active time-of-flight 3D imaging, consumer RGB-D cameras, and 3D data representation and visualisation; ● 3D shape analysis, including local descriptors, registration, matching, 3D morphable models, and deep learning on 3D datasets; and ● 3D applications, including 3D face recognition, cultural heritage and 3D phenotyping of plants. 3D computer vision is a rapidly advancing area in computer science. There are many real-world applications that demand high-performance 3D imaging and analysis and, as a result, many new techniques and commercial products have been developed. However, many challenges remain on how to analyse the captured data in a way that is sufficiently fast, robust and accurate for the application. Such challenges include metrology, semantic segmentation, classification and recognition. Thus, 3D imaging, analysis and their applications remain a highly-active research field that will continue to attract intensive attention from the research community with the ultimate goal of fully automating the 3D data capture, analysis and inference pipeline. .

Contents:

Introduction

Part I 3D Shape Acquisition, Representation and Visualization

Passive 3D Imaging

Active-triangulation 3D Imaging Systems for Industrial Inspection

Active Time-of-Flight 3D Imaging Systems for Medium-range Applications

Consumer-grade RGB-D cameras

3D Data Representation, Storage and Processing

Part II: 3D Shape Analysis and Inference

3D Local Descriptors

from Hand-crafted to Learned

3D Shape Registration

3D Shape Matching for Retrieval and Recognition

3D Morphable Models: the Face, Ear and Head

Deep Learning on 3D Data

Part III: 3D Imaging Applications

3D Face Recognition

3D Digitization of Cultural Heritage

3D Phenotyping of Plants

Index.

Other Format:

Printed edition:

ISBN:

978-3-030-44070-1

9783030440701

Access Restriction:

Restricted for use by site license.