This SpringerBrief presents novel methods of approaching challenging problems in the reconstruction of accurate 3D models and serves as an introduction for further 3D reconstruction methods. It develops a 3D reconstruction system that produces accurate results by cascading multiple novel loop detection, sifting, and optimization methods. The authors offer a fast point cloud registration method that utilizes optimized randomness in random sample consensus for surface loop detection. The text also proposes two methods for surface-loop sifting. One is supported by a sparse-feature-based optimization graph. This graph is more robust to different scan patterns than earlier methods and can cope with tracking failure and recovery. The other is an offline algorithm that can sift loop detections based on their impact on loop optimization results and which is enabled by a dense map posterior metric for 3D reconstruction and mapping performance evaluation works without any costly ground-truth data. The methods presented in Towards Optimal Point Cloud Processing for 3D Reconstruction will be of assistance to researchers developing 3D modelling methods and to workers in the wide variety of fields that exploit such technology including metrology, geological animation and mass customization in smart manufacturing.

This SpringerBrief presents novel methods of approaching challenging problems in the reconstruction of accurate 3D models and serves as an introduction for further 3D reconstruction methods. It develops a 3D reconstruction system that produces accurate results by cascading multiple novel loop detection, sifting, and optimization methods. The authors offer a fast point cloud registration method that utilizes optimized randomness in random sample consensus for surface loop detection. The text also proposes two methods for surface-loop sifting. One is supported by a sparse-feature-based optimization graph. This graph is more robust to different scan patterns than earlier methods and can cope with tracking failure and recovery. The other is an offline algorithm that can sift loop detections based on their impact on loop optimization results and which is enabled by a dense map posterior metric for 3D reconstruction and mapping performance evaluation works without any costly ground-truth data. The methods presented in Towards Optimal Point Cloud Processing for 3D Reconstruction will be of assistance to researchers developing 3D modelling methods and to workers in the wide variety of fields that exploit such technology including metrology, geological animation and mass customization in smart manufacturing.

This book brings together papers presented at the 2017 International Conference on Communications, Signal Processing, and Systems (ICCSP 2017), which was held on July 14–17, 2017 in Harbin, China. Presenting the latest developments and discussing the interactions and links between these multidisciplinary fields, the book spans topics ranging from communications, signal processing and systems. It is aimed at undergraduate and graduate electrical engineering, computer science and mathematics students, researchers and engineers from academia and industry as well as government employees.

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.

Vladislav Golyanik proposes several new methods for dense non-rigid structure from motion (NRSfM) as well as alignment of point clouds. The introduced methods improve the state of the art in various aspects, i.e. in the ability to handle inaccurate point tracks and 3D data with contaminations. NRSfM with shape priors obtained on-the-fly from several unoccluded frames of the sequence and the new gravitational class of methods for point set alignment represent the primary contributions of this book. About the Author: Vladislav Golyanik is currently a postdoctoral researcher at the Max Planck Institute for Informatics in Saarbrücken, Germany. The current focus of his research lies on 3D reconstruction and analysis of general deformable scenes, 3D reconstruction of human body and matching problems on point sets and graphs. He is interested in machine learning (both supervised and unsupervised), physics-based methods as well as new hardware and sensors for computer vision and graphics (e.g., quantum computers and event cameras).

Advances in Civil Function Structure and Industrial Architecture contains the Proceedings of 5th International Conference on Civil Function Structure and Industrial Architecture (CFSIA 2022), which was held on January 21-23, 2022, in Harbin, China. The Proceedings of CFSIA 2022 is intended to share scientific research results and cutting-edge technologies in the field of civil function structure and control engineering. Researchers, practitioners and academics in these disciplines will find the book useful. Over 90 papers are featured. Many topics are covered, but the contributions may be seen to fall into one of six broad themes of the conference, namely: (i) Engineering Structure (Engineering Advanced Technology, Engineering Structure and Seismic Resistance, High-rise Building and Large-span Structure, Bridge Engineering, Special Structure, Construction Technology, Monitoring and Control of Structure, Cartography and GIS, Concrete Structure, Construction and Control, etc.); (ii) Intelligent Building (Predictive Maintenance, Converged Networks, Wireless Retrofit, Biometric Integration, Computer Management System Engineering, Building Equipment Automatic Control System Engineering, etc.); (iii) Smart City (Intelligent Construction, Intelligent Transportation, Risk Management and Decision Making for Intelligent Construction, Intelligent Building Automation Control System, etc.); (iv) Structural Seismic Resistance (Structural Seismic Design, Earthquakes and Ground Motions, Building Site, Foundation and Basis, Principles of Structural Seismic Design Calculation, Seismic Shear Adjustment and Minimum Seismic Shear Requirements, etc.); (v) Monitoring and Testing (Steel Structure Stress Monitoring, Stress Change Monitoring for Large Construction Projects, Structural Health Monitoring, Foundation Pit Monitoring, Temperature Monitoring for Large Volume Concrete Pouring, etc.); (vi) Engineering Facility (Machinery Facility, Electrical Facility, Stationary Facility, Non-standard Facility, Compressor, Continuous Transmission Facility, etc.).

This book constitutes the proceedings of the 12th International Congress on Telematics and Computing, WITCOM 2023, held in Puerto Vallarta, Mexico, in November 2023. The 35 full papers presented in this volume were carefully reviewed and selected from 88 submissions. The papers are focused on the topics of artificial intelligence techniques, data science, blockchain, environment monitoring, cybersecurity, education, and software for communications protocols.