3D Imaging, Analysis and Applications

This textbook is designed for postgraduate studies in 3D Computer Vision and provides a useful reference for industrial practitioners. It covers three main areas: 3D imaging, 3D shape analysis, and 3D applications, and includes new material on consumer-grade RGB-D cameras, 3D morphable models, deep learning on 3D datasets, and new applications in 3D digitization of cultural heritage and 3D phenotyping of crops. 3D computer vision is a rapidly advancing area with many real-world applications, but challenges remain in analyzing captured data efficiently and accurately.

Format: Paperback / softback
Length: 736 pages
Publication date: 13 September 2021
Publisher: Springer Nature Switzerland AG

This comprehensive textbook is meticulously crafted for postgraduate studies in the dynamic field of 3D Computer Vision. It serves as an invaluable resource for both industrial practitioners and academic enthusiasts alike, particularly in the domains of 3D data capture, computer-aided geometric modelling, and industrial quality assurance. This second edition represents a substantial enhancement of existing topics, complemented by novel discoveries. Furthermore, it introduces fresh content covering consumer-grade RGB-D cameras, 3D morphable models, the application of deep learning on 3D datasets, as well as innovative applications in the 3D digitization of cultural heritage and the 3D phenotyping of crops.

The book is organized into three principal sections:
1. 3D Imaging: This section encompasses a wide range of 3D imaging techniques, including passive 3D imaging, active triangulation 3D imaging, active time-of-flight 3D imaging, consumer RGB-D cameras, and 3D data representation and visualisation. It delves into the fundamentals of capturing and processing 3D data, exploring the various technologies and algorithms employed to obtain high-quality 3D images.
2. 3D Shape Analysis: This section focuses on the analysis of 3D shapes and structures. It covers essential topics such as local descriptors, registration, matching, 3D morphable models, and the utilization of deep learning on 3D datasets. It explores the techniques and algorithms used to extract meaningful information from 3D data, enabling tasks such as object recognition, semantic segmentation, and shape classification.
3. 3D Applications: This section showcases the diverse applications of 3D computer vision in various fields. It explores the use of 3D imaging and analysis in areas such as 3D face recognition, cultural heritage preservation, and 3D phenotyping of plants. It discusses the state-of-the-art techniques and algorithms employed to address real-world problems and achieve groundbreaking results.

The field of 3D computer vision is experiencing a remarkable surge in progress and innovation. With numerous real-world applications demanding high-performance 3D imaging and analysis, there is an urgent need for new techniques and commercial products to meet these demands. However, several challenges remain in analysing the captured data efficiently, robustly, and accurately. These challenges encompass areas such as metrology, semantic segmentation, classification, and recognition. As a result, 3D imaging, analysis, and their applications continue to be a highly active research field, drawing significant attention from the research community. The ultimate goal is to automate the entire 3D data capture, analysis, and inference pipeline, enabling seamless and efficient processing of 3D data for a wide range of applications.

In conclusion, this textbook is a vital resource for anyone seeking to delve into the realm of 3D Computer Vision. It provides a comprehensive and up-to-date coverage of the field, encompassing 3D imaging, shape analysis, and applications. Whether you are an academic researcher, an industrial practitioner, or simply a curious enthusiast, this book will empower you with the knowledge and tools necessary to excel in this rapidly evolving field.

Weight: 1128g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030440725
Edition number: 2nd ed. 2020