3D Point Cloud Analysis

3D Point Cloud Analysis PDF Author: Shan Liu
Publisher: Springer Nature
ISBN: 3030891801
Category : Computers
Languages : en
Pages : 156

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Book Description
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.

3D Point Cloud Analysis

3D Point Cloud Analysis PDF Author: Shan Liu
Publisher: Springer Nature
ISBN: 3030891801
Category : Computers
Languages : en
Pages : 156

Get Book Here

Book Description
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.

Reconstruction and Analysis of 3D Scenes

Reconstruction and Analysis of 3D Scenes PDF Author: Martin Weinmann
Publisher: Springer
ISBN: 3319292463
Category : Computers
Languages : en
Pages : 250

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Book Description
This unique work presents a detailed review of the processing and analysis of 3D point clouds. A fully automated framework is introduced, incorporating each aspect of a typical end-to-end processing workflow, from raw 3D point cloud data to semantic objects in the scene. For each of these components, the book describes the theoretical background, and compares the performance of the proposed approaches to that of current state-of-the-art techniques. Topics and features: reviews techniques for the acquisition of 3D point cloud data and for point quality assessment; explains the fundamental concepts for extracting features from 2D imagery and 3D point cloud data; proposes an original approach to keypoint-based point cloud registration; discusses the enrichment of 3D point clouds by additional information acquired with a thermal camera, and describes a new method for thermal 3D mapping; presents a novel framework for 3D scene analysis.

Morphological Plant Modeling: Unleashing Geometric and Topological Potential within the Plant Sciences

Morphological Plant Modeling: Unleashing Geometric and Topological Potential within the Plant Sciences PDF Author: Alexander Bucksch
Publisher: Frontiers Media SA
ISBN: 2889452972
Category :
Languages : en
Pages : 298

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Book Description
An increasing population faces the growing demand for agricultural products and accurate global climate models that account for individual plant morphologies to predict favorable human habitat. Both demands are rooted in an improved understanding of the mechanistic origins of plant development. Such understanding requires geometric and topological descriptors to characterize the phenotype of plants and its link to genotypes. However, the current plant phenotyping framework relies on simple length and diameter measurements, which fail to capture the exquisite architecture of plants. The Research Topic “Morphological Plant Modeling: Unleashing Geometric and Topological Potential within the Plant Sciences” is the result of a workshop held at National Institute for Mathematical and Biological Synthesis (NIMBioS) in Knoxville, Tennessee. From 2.-4. September 2015 over 40 scientists from mathematics, computer science, engineering, physics and biology came together to set new frontiers in combining plant phenotyping with recent results from shape theory at the interface of geometry and topology. In doing so, the Research Topic synthesizes the views from multiple disciplines to reveal the potential of new mathematical concepts to analyze and quantify the relationship between morphological plant features. As such, the Research Topic bundles examples of new mathematical techniques including persistent homology, graph-theory, and shape statistics to tackle questions in crop breeding, developmental biology, and vegetation modeling. The challenge to model plant morphology under field conditions is a central theme of the included papers to address the problems of climate change and food security, that require the integration of plant biology and mathematics from geometry and topology research applied to imaging and simulation techniques. The introductory white paper written by the workshop participants identifies future directions in research, education and policy making to integrate biological and mathematical approaches and to strengthen research at the interface of both disciplines.

Computer Vision – ECCV 2018 Workshops

Computer Vision – ECCV 2018 Workshops PDF Author: Laura Leal-Taixé
Publisher: Springer
ISBN: 303011015X
Category : Computers
Languages : en
Pages : 763

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Book Description
The six-volume set comprising the LNCS volumes 11129-11134 constitutes the refereed proceedings of the workshops that took place in conjunction with the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.43 workshops from 74 workshops proposals were selected for inclusion in the proceedings. The workshop topics present a good orchestration of new trends and traditional issues, built bridges into neighboring fields, and discuss fundamental technologies and novel applications.

Intelligent Data analysis and its Applications, Volume I

Intelligent Data analysis and its Applications, Volume I PDF Author: Jeng-Shyang Pan
Publisher: Springer
ISBN: 9783319077758
Category : Computers
Languages : en
Pages : 0

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Book Description
This volume presents the proceedings of the First Euro-China Conference on Intelligent Data Analysis and Applications (ECC 2014), which was hosted by Shenzhen Graduate School of Harbin Institute of Technology and was held in Shenzhen City on June 13-15, 2014. ECC 2014 was technically co-sponsored by Shenzhen Municipal People’s Government, IEEE Signal Processing Society, Machine Intelligence Research Labs, VSB-Technical University of Ostrava (Czech Republic), National Kaohsiung University of Applied Sciences (Taiwan), and Secure E-commerce Transactions (Shenzhen) Engineering Laboratory of Shenzhen Institute of Standards and Technology.

Point-Based Graphics

Point-Based Graphics PDF Author: Markus Gross
Publisher: Elsevier
ISBN: 0080548822
Category : Computers
Languages : en
Pages : 553

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Book Description
The polygon-mesh approach to 3D modeling was a huge advance, but today its limitations are clear. Longer render times for increasingly complex images effectively cap image complexity, or else stretch budgets and schedules to the breaking point. Comprised of contributions from leaders in the development and application of this technology, Point-Based Graphics examines it from all angles, beginning with the way in which the latest photographic and scanning devices have enabled modeling based on true geometry, rather than appearance. From there, it's on to the methods themselves. Even though point-based graphics is in its infancy, practitioners have already established many effective, economical techniques for achieving all the major effects associated with traditional 3D Modeling and rendering. You'll learn to apply these techniques, and you'll also learn how to create your own. The final chapter demonstrates how to do this using Pointshop3D, an open-source tool for developing new point-based algorithms. - The first book on a major development in computer graphics by the pioneers in the field - Shows how 3D images can be manipulated as easily as 2D images are with Photoshop

A Review of Point Cloud Registration Algorithms for Mobile Robotics

A Review of Point Cloud Registration Algorithms for Mobile Robotics PDF Author: Francois Pomerleau
Publisher:
ISBN: 9781680830248
Category : Technology & Engineering
Languages : en
Pages : 122

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Book Description
Deals with the topic of geometric registration in robotics. It provides a historical perspective of the registration problem and shows that the various solutions available can be organized and differentiated in a framework according to a few elements. It also reviews a few applications of this framework in mobile robotics.

3D Computer Vision

3D Computer Vision PDF Author: Christian Wöhler
Publisher: Springer Science & Business Media
ISBN: 3642017320
Category : Computers
Languages : en
Pages : 391

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Book Description
This work provides an introduction to the foundations of three-dimensional c- puter vision and describes recent contributions to the ?eld, which are of methodical and application-speci?c nature. Each chapter of this work provides an extensive overview of the corresponding state of the art, into which a detailed description of new methods or evaluation results in application-speci?c systems is embedded. Geometric approaches to three-dimensional scene reconstruction (cf. Chapter 1) are primarily based on the concept of bundle adjustment, which has been developed more than 100 years ago in the domain of photogrammetry. The three-dimensional scene structure and the intrinsic and extrinsic camera parameters are determined such that the Euclidean backprojection error in the image plane is minimised, u- ally relying on a nonlinear optimisation procedure. In the ?eld of computer vision, an alternative framework based on projective geometry has emerged during the last two decades, which allows to use linear algebra techniques for three-dimensional scene reconstructionand camera calibration purposes. With special emphasis on the problems of stereo image analysis and camera calibration, these fairly different - proaches are related to each other in the presented work, and their advantages and drawbacks are stated. In this context, various state-of-the-artcamera calibration and self-calibration methods as well as recent contributions towards automated camera calibration systems are described. An overview of classical and new feature-based, correlation-based, dense, and spatio-temporal methods for establishing point c- respondences between pairs of stereo images is given.

Artificial Neural Networks and Machine Learning – ICANN 2022

Artificial Neural Networks and Machine Learning – ICANN 2022 PDF Author: Elias Pimenidis
Publisher: Springer Nature
ISBN: 3031159349
Category : Computers
Languages : en
Pages : 835

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Book Description
The 4-volumes set of LNCS 13529, 13530, 13531, and 13532 constitutes the proceedings of the 31st International Conference on Artificial Neural Networks, ICANN 2022, held in Bristol, UK, in September 2022. The total of 255 full papers presented in these proceedings was carefully reviewed and selected from 561 submissions. ICANN 2022 is a dual-track conference featuring tracks in brain inspired computing and machine learning and artificial neural networks, with strong cross-disciplinary interactions and applications.

Advances in Computer Graphics

Advances in Computer Graphics PDF Author: Bin Sheng
Publisher: Springer Nature
ISBN: 3031500784
Category : Computers
Languages : en
Pages : 409

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Book Description
This 4-volume set of LNCS 14495-14498 constitutes the proceedings of the 40th Computer Graphics International Conference, CGI 2023, held in Shanghai, China, August 28 – September 1, 2023. The 149 papers in this set were carefully reviewed and selected from 385 submissions. They are organized in topical sections as follows: Detection and Recognition; Image Analysis and Processing; Image Restoration and Enhancement; Image Attention and Perception; Reconstruction; Rendering and Animation; Synthesis and Generation; Visual Analytics and Modeling; Graphics and AR/VR; Medical Imaging and Robotics; Theoretical Analysis; Image Analysis and Visualization in Advanced Medical Imaging Technology; Empowering Novel Geometric Algebra for Graphics and Engineering.