Deep Learning For 3d Point Clouds
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Deep Learning For 3d Point Clouds
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Author : Wei Gao
language : en
Publisher: Springer Nature
Release Date : 2024-12-06
Deep Learning For 3d Point Clouds written by Wei Gao and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-06 with Computers categories.
As an efficient 3D vision solution, point clouds have been widely applied into diverse engineering scenarios, including immersive media communication, autonomous driving, reverse engineering, robots, topography mapping, digital twin city, medical analysis, digital museum, etc. Thanks to the great developments of deep learning theories and methods, 3D point cloud technologies have undergone fast growth during the past few years, including diverse processing and understanding tasks. Human and machine perception can be benefited from the success of using deep learning approaches, which can significantly improve 3D perception modeling and optimization, as well as 3D pre-trained and large models. This book delves into these research frontiers of deep learning-based point cloud technologies. The subject of this book focuses on diverse intelligent processing technologies for the fast-growing 3D point cloud applications, especially using deep learning-based approaches. The deep learning-based enhancement and analysis methods are elaborated in detail, as well as the pre-trained and large models with 3D point clouds. This book carefully presents and discusses the newest progresses in the field of deep learning-based point cloud technologies, including basic concepts, fundamental background knowledge, enhancement, analysis, 3D pre-trained and large models, multi-modal learning, open source projects, engineering applications, and future prospects. Readers can systematically learn the knowledge and the latest developments in the field of deep learning-based point cloud technologies. This book provides vivid illustrations and examples, and the intelligent processing methods for 3D point clouds. Readers can be equipped with an in-depth understanding of the latest advancements of this rapidly developing research field.
3d Point Cloud Analysis
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Author : Shan Liu
language : en
Publisher: Springer Nature
Release Date : 2021-12-10
3d Point Cloud Analysis written by Shan Liu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-10 with Computers categories.
This book introduces the point cloud; its applications in industry, and the most frequently used datasets. It mainly focuses on three computer vision tasks -- point cloud classification, segmentation, and registration -- which are fundamental to any point cloud-based system. An overview of traditional point cloud processing methods helps readers build background knowledge quickly, while the deep learning on point clouds methods include comprehensive analysis of the breakthroughs from the past few years. Brand-new explainable machine learning methods for point cloud learning, which are lightweight and easy to train, are then thoroughly introduced. Quantitative and qualitative performance evaluations are provided. The comparison and analysis between the three types of methods are given to help readers have a deeper understanding. With the rich deep learning literature in 2D vision, a natural inclination for 3D vision researchers is to develop deep learning methods for point cloud processing. Deep learning on point clouds has gained popularity since 2017, and the number of conference papers in this area continue to increase. Unlike 2D images, point clouds do not have a specific order, which makes point cloud processing by deep learning quite challenging. In addition, due to the geometric nature of point clouds, traditional methods are still widely used in industry. Therefore, this book aims to make readers familiar with this area by providing comprehensive overview of the traditional methods and the state-of-the-art deep learning methods. A major portion of this book focuses on explainable machine learning as a different approach to deep learning. The explainable machine learning methods offer a series of advantages over traditional methods and deep learning methods. This is a main highlight and novelty of the book. By tackling three research tasks -- 3D object recognition, segmentation, and registration using our methodology -- readers will have a sense of how to solve problems in a different way and can apply the frameworks to other 3D computer vision tasks, thus give them inspiration for their own future research. Numerous experiments, analysis and comparisons on three 3D computer vision tasks (object recognition, segmentation, detection and registration) are provided so that readers can learn how to solve difficult Computer Vision problems.
Topographic Laser Ranging And Scanning
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Author : Jie Shan
language : en
Publisher: CRC Press
Release Date : 2017-12-19
Topographic Laser Ranging And Scanning written by Jie Shan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-19 with Technology & Engineering categories.
A systematic, in-depth introduction to theories and principles of Light Detection and Ranging (LiDAR) technology is long overdue, as it is the most important geospatial data acquisition technology to be introduced in recent years. An advanced discussion, this text fills the void. Professionals in fields ranging from geology, geography and geoinformatics to physics, transportation, and law enforcement will benefit from this comprehensive discussion of topographic LiDAR principles, systems, data acquisition, and data processing techniques. The book covers ranging and scanning fundamentals, and broad, contemporary analysis of airborne LiDAR systems, as well as those situated on land and in space. The authors present data collection at the signal level in terms of waveforms and their properties; at the system level with regard to calibration and georeferencing; and at the data level to discuss error budget, quality control, and data organization. They devote the bulk of the book to LiDAR data processing and information extraction and elaborate on recent developments in building extraction and reconstruction, highlighting quality and performance evaluations. There is also extensive discussion of the state-of-the-art technological developments used in: filtering algorithms for digital terrain model generation; strip adjustment of data for registration; co-registration of LiDAR data with imagery; forestry inventory; and surveying. Readers get insight into why LiDAR is the effective tool of choice to collect massive volumes of explicit 3-D data with unprecedented accuracy and simplicity. Compiled by leading experts talking about much of their own pioneering work, this book will give researchers, professionals, and senior students novel ideas to supplement their own experience and practices.
Computer Vision Eccv 2024
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Author : Aleš Leonardis
language : en
Publisher: Springer Nature
Release Date : 2024-10-02
Computer Vision Eccv 2024 written by Aleš Leonardis and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-02 with Computers categories.
The multi-volume set of LNCS books with volume numbers 15059 up to 15147 constitutes the refereed proceedings of the 18th European Conference on Computer Vision, ECCV 2024, held in Milan, Italy, during September 29–October 4, 2024. The 2387 papers presented in these proceedings were carefully reviewed and selected from a total of 8585 submissions. They deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; motion estimation.
Multimodal Panoptic Segmentation Of 3d Point Clouds
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Author : Dürr, Fabian
language : en
Publisher: KIT Scientific Publishing
Release Date : 2023-10-09
Multimodal Panoptic Segmentation Of 3d Point Clouds written by Dürr, Fabian and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-09 with categories.
The understanding and interpretation of complex 3D environments is a key challenge of autonomous driving. Lidar sensors and their recorded point clouds are particularly interesting for this challenge since they provide accurate 3D information about the environment. This work presents a multimodal approach based on deep learning for panoptic segmentation of 3D point clouds. It builds upon and combines the three key aspects multi view architecture, temporal feature fusion, and deep sensor fusion.
Ubiquitous Point Cloud
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Author : Bisheng Yang
language : en
Publisher: CRC Press
Release Date : 2024-12-04
Ubiquitous Point Cloud written by Bisheng Yang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-04 with Technology & Engineering categories.
Point clouds from LiDAR and photogrammetry are vital and vast sources of geospatial information besides remote sensing imagery. This book provides the latest theory and methodology for point cloud processing with AI to better serve earth observation, 3D vision, autonomous driving, smart city, and geospatial information applications. It covers various aspects of 3D geospatial information, including data capturing, fusing, geocomputing, modeling, and vast downstream applications. With the inclusion of numerous illustrations, diagrams, and practical applications, readers will better understand the point cloud, and its technical challenges, and learn how to utilize point cloud in different fields. Features Provides in-depth point cloud processing pipeline, cutting-edge theory, and technology with AI. Includes many specific applications of point cloud in the geospatial field. Offers a comprehensive step-by-step guide from theory to application in point cloud processing. Includes ample supplementary materials including datasets, tools, and other online resources. Helps readers across many disciplines, from geospatial to engineering, to understand the vast application of point clouds and how to further generate new ideas and innovative thoughts. This book is an excellent resource for researchers, academics, students, and professionals in a variety of fields including Geomatics, Remote Sensing, Cartography and Geographic Information Systems, Data Science, Geography, Earth Science, and more.
3d Data Science With Python
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Author : Florent Poux
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-04-09
3d Data Science With Python written by Florent Poux and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-09 with Computers categories.
Our physical world is grounded in three dimensions. To create technology that can reason about and interact with it, our data must be 3D too. This practical guide offers data scientists, engineers, and researchers a hands-on approach to working with 3D data using Python. From 3D reconstruction to 3D deep learning techniques, you'll learn how to extract valuable insights from massive datasets, including point clouds, voxels, 3D CAD models, meshes, images, and more. Dr. Florent Poux helps you leverage the potential of cutting-edge algorithms and spatial AI models to develop production-ready systems with a focus on automation. You'll get the 3D data science knowledge and code to: Understand core concepts and representations of 3D data Load, manipulate, analyze, and visualize 3D data using powerful Python libraries Apply advanced AI algorithms for 3D pattern recognition (supervised and unsupervised) Use 3D reconstruction techniques to generate 3D datasets Implement automated 3D modeling and generative AI workflows Explore practical applications in areas like computer vision/graphics, geospatial intelligence, scientific computing, robotics, and autonomous driving Build accurate digital environments that spatial AI solutions can leverage Florent Poux is an esteemed authority in the field of 3D data science who teaches and conducts research for top European universities. He's also head professor at the 3D Geodata Academy and innovation director for French Tech 120 companies.
Computer Vision Eccv 2020 Workshops
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Author : Adrien Bartoli
language : en
Publisher: Springer Nature
Release Date : 2021-01-09
Computer Vision Eccv 2020 Workshops written by Adrien Bartoli and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-09 with Computers categories.
The 6-volume set, comprising the LNCS books 12535 until 12540, constitutes the refereed proceedings of 28 out of the 45 workshops held at the 16th European Conference on Computer Vision, ECCV 2020. The conference was planned to take place in Glasgow, UK, during August 23-28, 2020, but changed to a virtual format due to the COVID-19 pandemic. The 249 full papers, 18 short papers, and 21 further contributions included in the workshop proceedings were carefully reviewed and selected from a total of 467 submissions. The papers deal with diverse computer vision topics. Part I focusses on adversarial robustness in the real world; bioimage computation; egocentric perception, interaction and computing; eye gaze in VR, AR, and in the wild; TASK-CV workshop and VisDA challenge; and bodily expressed emotion understanding.
Proceedings Of 3rd 2023 International Conference On Autonomous Unmanned Systems 3rd Icaus 2023
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Author : Yi Qu
language : en
Publisher: Springer Nature
Release Date : 2024-04-22
Proceedings Of 3rd 2023 International Conference On Autonomous Unmanned Systems 3rd Icaus 2023 written by Yi Qu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-22 with Technology & Engineering categories.
This book includes original, peer-reviewed research papers from the 3rd ICAUS 2023, which provides a unique and engaging platform for scientists, engineers and practitioners from all over the world to present and share their most recent research results and innovative ideas. The 3rd ICAUS 2023 aims to stimulate researchers working in areas relevant to intelligent unmanned systems. Topics covered include but are not limited to: Unmanned Aerial/Ground/Surface/Underwater Systems, Robotic, Autonomous Control/Navigation and Positioning/ Architecture, Energy and Task Planning and Effectiveness Evaluation Technologies, Artificial Intelligence Algorithm/Bionic Technology and their Application in Unmanned Systems. The papers presented here share the latest findings in unmanned systems, robotics, automation, intelligent systems, control systems, integrated networks, modelling and simulation. This makes the book a valuable resource for researchers, engineers and students alike.
3d Imaging Analysis And Applications
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Author : Yonghuai Liu
language : en
Publisher: Springer Nature
Release Date : 2020-09-11
3d Imaging Analysis And Applications written by Yonghuai Liu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-11 with Computers categories.
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.