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Automatic Generation of a 3D City Model
UNIVERSITY OF CASTILLA-LA MANCHA ESCUELA SUPERIOR DE INFORMÁTICA COMPUTER ENGINEERING DEGREE DEGREE FINAL PROJECT Automatic generation of a 3D city model David Murcia Pacheco June, 2017 AUTOMATIC GENERATION OF A 3D CITY MODEL Escuela Superior de Informática UNIVERSITY OF CASTILLA-LA MANCHA ESCUELA SUPERIOR DE INFORMÁTICA Information Technology and Systems SPECIFIC TECHNOLOGY OF COMPUTER ENGINEERING DEGREE FINAL PROJECT Automatic generation of a 3D city model Author: David Murcia Pacheco Director: Dr. Félix Jesús Villanueva Molina June, 2017 David Murcia Pacheco Ciudad Real – Spain E-mail: [email protected] Phone No.:+34 625 922 076 c 2017 David Murcia Pacheco Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.3 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license is included in the section entitled "GNU Free Documentation License". i TRIBUNAL: Presidente: Vocal: Secretario: FECHA DE DEFENSA: CALIFICACIÓN: PRESIDENTE VOCAL SECRETARIO Fdo.: Fdo.: Fdo.: ii Abstract HIS document collects all information related to the Degree Final Project (DFP) of Com- T puter Engineering Degree of the student David Murcia Pacheco, tutorized by Dr. Félix Jesús Villanueva Molina. This work has been developed during 2016 and 2017 in the Escuela Superior de Informática (ESI), in Ciudad Real, Spain. It is based in one of the proposed sub- jects by the faculty of this university for this year, called "Generación automática del modelo en 3D de una ciudad". -
Cloudcompare Point Cloud Processing Workshop Daniel Girardeau-Montaut
CloudCompare Point Cloud Processing Workshop Daniel Girardeau-Montaut www.cloudcompare.org @CloudCompareGPL PCP 2019 [email protected] December 4-5, 2019, Stuttgart, Germany Outline About the project Quick overview of the software capabilities Point cloud processing with CloudCompare The project 2003: PhD for EDF R&D EDF Main French power utility More than 150 000 employees worldwide 2 000 @ R&D (< 2%) 200 know about CloudCompare (< 0.2%) Sales >75 B€ > 200 dams + 58 nuclear reactors (19 plants) EDF and Laser Scanning EDF = former owner of Mensi (now Trimble Laser Scanning) Main scanning activity: as-built documentation Scanning a single nuclear reactor building 2002: 3 days, 50 M. points 2014: 1.5 days, 50 Bn points (+ high res. photos) EDF and Laser Scanning Other scanning activities: Building monitoring (dams, cooling towers, etc.) Landslide monitoring Hydrology Historical preservation (EDF Foundation) PhD Change detection on 3D geometric data Application to Emergency Mapping Inspired by 9/11 post-attacks recovery efforts (see “Mapping Ground Zero” by J. Kern, Optech, Nov. 2001) TLS was used for: visualization, optimal crane placement, measurements, monitoring the subsidence of the wreckage pile, slurry wall monitoring, etc. CloudCompare V1 2004-2006 Aim: quickly detecting changes by comparing TLS point clouds… with a CAD mesh or with another (high density) cloud CloudCompare V2 2007: “Industrialization” of CloudCompare … for internal use only! Rationale: idle reactor = 6 M€ / day acquired data -
Seamless Texture Mapping of 3D Point Clouds
Seamless Texture Mapping of 3D Point Clouds Dan Goldberg Mentor: Carl Salvaggio Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology Rochester, NY November 25, 2014 Abstract The two similar, quickly growing fields of computer vision and computer graphics give users the ability to immerse themselves in a realistic computer generated environment by combining the ability create a 3D scene from images and the texture mapping process of computer graphics. The output of a popular computer vision algorithm, structure from motion (obtain a 3D point cloud from images) is incomplete from a computer graphics standpoint. The final product should be a textured mesh. The goal of this project is to make the most aesthetically pleasing output scene. In order to achieve this, auxiliary information from the structure from motion process was used to texture map a meshed 3D structure. 1 Introduction The overall goal of this project is to create a textured 3D computer model from images of an object or scene. This problem combines two different yet similar areas of study. Computer graphics and computer vision are two quickly growing fields that take advantage of the ever-expanding abilities of our computer hardware. Computer vision focuses on a computer capturing and understanding the world. Computer graphics con- centrates on accurately representing and displaying scenes to a human user. In the computer vision field, constructing three-dimensional (3D) data sets from images is becoming more common. Microsoft's Photo- synth (Snavely et al., 2006) is one application which brought attention to the 3D scene reconstruction field. Many structure from motion algorithms are being applied to data sets of images in order to obtain a 3D point cloud (Koenderink and van Doorn, 1991; Mohr et al., 1993; Snavely et al., 2006; Crandall et al., 2011; Weng et al., 2012; Yu and Gallup, 2014; Agisoft, 2014). -
TUESDAY MORNING Open Open Open
TUESDAY MORNING Open Open Open. The Rise of Open Scientific Publishing and the 8:30 AM Keynote Address Dr. Ken Kvamme Archaeological Discipline: Managing the Paradigm Shift SCE Auditorium Education and Dissemination 9:30 AM Coffee Break Room: SCE 216 Organizers: Arianna Traviglia, Xavier Rodier General Papers 9:50 AM RocksMacqueen, Doug, Tom Levy, The Last of the Publishers General GIS 10:10 AM RouedCunliffe, Henriette, Peter Room: SCE House Jensen, What is Open Data in an Archaeological Context? 9:50 AM Caswell, Edward, An Analysis of 10:30 AM Brin, Adam, Francis Pierce Selected Variables that Affect the McManamon, Leigh Anne Ellison, The Production of Cost Surfaces Challenges of Open Access for 10:10 AM Becker, Daniel, Christian Willmes, Archaeological Repositories Andreas Bolten, María de Andrés 10:50 AM Kondo, Yasuhisa, Atsushi Noguchi, Herrero, GerdChristian Weniger, Best Practices and Challenges in Georg Bareth, Influence of Differences Promoting Open Science in in Digital Elevation Models and their Archaeology: Two Narratives from Resolution on SlopeBased Site Japan Catchment Modelling 11:10 AM Rodier, Xavier, Olivier Marlet, How to 10:30 AM Beusing, Ruth, TemporalGIS Tools for Combine Archaeological Archives, Mixed and MesoScale Archaeological Linked Open Data and Academic Data Publication, a French Experience 10:50 AM James, Vivian, Context as Theory: 11:30 AM Buard, PierreYves, Elisabeth Zadora Towards Unification of Computer Rio, Publishing an Archaeological Applications and Quantitative Methods Excavation Report in a Logicist in Archaeology Workflow 11:10 AM Sharp, Kayeleigh, Testing the ‘Small 11:50 AM Kansa, Eric, Anne Austin, Ixchel Site’ Approach with Multivariate Spatial Faniel, Sarah Kansa, Ran Boynter, Statistical and Archaeological Network Jennifer Jacobs, Phoebe France, A Analysis Reality Check: The Impact of Open Data in Archaeology 11:30 AM Groen, Mike, Geospatial Analysis, Predictive Modelling and Modern Clandestine Burials Same as it ever was.. -
Simulated Imagery Rendering Workflow for UAS-Based
remote sensing Article Simulated Imagery Rendering Workflow for UAS-Based Photogrammetric 3D Reconstruction Accuracy Assessments Richard K. Slocum * and Christopher E. Parrish School of Civil and Construction Engineering, Oregon State University, 101 Kearney Hall, 1491 SW Campus Way, Corvallis, OR 97331, USA; [email protected] * Correspondence: [email protected]; Tel.: +1-703-973-1983 Academic Editors: Gonzalo Pajares Martinsanz, Xiaofeng Li and Prasad S. Thenkabail Received: 13 March 2017; Accepted: 19 April 2017; Published: 22 April 2017 Abstract: Structure from motion (SfM) and MultiView Stereo (MVS) algorithms are increasingly being applied to imagery from unmanned aircraft systems (UAS) to generate point cloud data for various surveying and mapping applications. To date, the options for assessing the spatial accuracy of the SfM-MVS point clouds have primarily been limited to empirical accuracy assessments, which involve comparisons against reference data sets, which are both independent and of higher accuracy than the data they are being used to test. The acquisition of these reference data sets can be expensive, time consuming, and logistically challenging. Furthermore, these experiments are also almost always unable to be perfectly replicated and can contain numerous confounding variables, such as sun angle, cloud cover, wind, movement of objects in the scene, and camera thermal noise, to name a few. The combination of these factors leads to a situation in which robust, repeatable experiments are cost prohibitive, and the experiment results are frequently site-specific and condition-specific. Here, we present a workflow to render computer generated imagery using a virtual environment which can mimic the independent variables that would be experienced in a real-world UAS imagery acquisition scenario. -
Objekttracking Für Dynamisches Videoprojektions Mapping
Bachelorthesis Iwer Petersen Using object tracking for dynamic video projection mapping Fakultät Technik und Informatik Faculty of Engineering and Computer Science Studiendepartment Informatik Department of Computer Science Iwer Petersen Using object tracking for dynamic video projection mapping Bachelorthesis submitted within the scope of the Bachelor examination in the degree programme Bachelor of Science Technical Computer Science at the Department of Computer Science of the Faculty of Engineering and Computer Science of the Hamburg University of Applied Science Mentoring examiner: Prof. Dr. Ing. Birgit Wendholt Second expert: Prof. Dr.-Ing. Andreas Meisel Submitted at: January 31, 2013 Iwer Petersen Title of the paper Using object tracking for dynamic video projection mapping Keywords video projection mapping, object tracking, point cloud, 3D Abstract This document presents a way to realize video projection mapping onto moving objects. Therefore a visual 3D tracking method is used to determine the position and orientation of a known object. Via a calibrated projector-camera system, the real object then is augmented with a virtual texture. Iwer Petersen Thema der Arbeit Objekttracking für dynamisches Videoprojektions Mapping Stichworte Video Projektions Mapping, Objektverfolgung, Punktwolke, 3D Kurzzusammenfassung Dieses Dokument präsentiert einen Weg um Video Projektions Mapping auf sich bewegende Objekte zu realisieren. Dafür wird ein visuelles 3D Trackingverfahren verwendet um die Position und Lage eines bekannten Objekts zu bestimmen. Über ein kalibriertes Projektor- Kamera System wird das reale Objekt dann mit einer virtuellen Textur erweitert. Contents 1 Introduction1 1.1 Motivation . .1 1.2 Structure . .3 2 Related Work4 2.1 Corresponding projects . .4 2.1.1 Spatial Augmented Reality . .4 2.1.2 2D Mapping onto people . -
Room Layout Estimation on Mobile Devices
En vue de l'obtention du DOCTORAT DE L'UNIVERSITÉ DE TOULOUSE Délivré par : Institut National Polytechnique de Toulouse (Toulouse INP) Discipline ou spécialité : Image, Information et Hypermédia Présentée et soutenue par : M. VINCENT ANGLADON le vendredi 27 avril 2018 Titre : Room layout estimation on mobile devices Ecole doctorale : Mathématiques, Informatique, Télécommunications de Toulouse (MITT) Unité de recherche : Institut de Recherche en Informatique de Toulouse (I.R.I.T.) Directeur(s) de Thèse : M. VINCENT CHARVILLAT M. SIMONE GASPARINI Rapporteurs : M. CARSTEN GRIWODZ, UNIVERSITE D'OSLO M. DAVID FOFI, UNIVERSITE DE BOURGOGNE Membre(s) du jury : Mme LUCE MORIN, INSA DE RENNES, Président M. PASCAL BERTOLINO, UNIVERSITE GRENOBLE ALPES, Membre M. SIMONE GASPARINI, INP TOULOUSE, Membre M. TOMISLAV PRIBANIC, UNIVERSITE DE ZAGREB, Membre M. VINCENT CHARVILLAT, INP TOULOUSE, Membre Acknowledgments I would like to thank my thesis committee for giving me the opportunity to work on an exciting topic, and for the trust they placed in me. First, Simone Gasparini, I had the pleasure to have as advisor, who kept a cautious eye on my scientific and technical productions. I am certain this great attention to the details played an important role in the quality of my publications and the absence of rejection notice. Then, my thesis director, Vincent Charvillat, who was always generous in original ideas and positive energy. His advice helped me to put a more flattering light on my works and feel more optimistic. Finally, Telequid, which funded my works, with a special thought to Frédéric Bruel and Benjamin Ahsan for their great patience. I would also like to thank my referees: Prof. -
Basic Implementation and Measurements of Plane Detection
Basic Implementation and Measurements of Plane Detection in Point Clouds A project of the 2017 Robotics Course of the School of Information Science and Technology (SIST) of ShanghaiTech University https://robotics.shanghaitech.edu.cn/teaching/robotics2017 Chen Chen Wentao Lv Yuan Yuan School of Information and School of Information and School of Information and Science Technology Science Technology Science Technology [email protected] [email protected] [email protected] ShanghaiTech University ShanghaiTech University ShanghaiTech University Abstract—In practical robotics research, plane detection is an Corsini et al.(2012) is working on dealing with the problem important prerequisite to a wide variety of vision tasks. FARO is of taking random samples over the surface of a 3D mesh another powerful devices to scan the whole environment into describing and evaluating efficient algorithms for generating point cloud. In our project, we are working to apply some algorithms to convert point cloud data to plane mesh, and then different distributions. In this paper, the author we propose path planning based on the plane information. Constrained Poisson-disk sampling, a new Poisson-disk sam- pling scheme for polygonal meshes which can be easily I. Introduction tweaked in order to generate customized set of points such as In practical robotics research, plane detection is an im- importance sampling or distributions with generic geometric portant prerequisite to a wide variety of vision tasks. Plane constraints. detection means to detect the plane information from some Kazhdan and Hoppe(2013) is talking about poisson surface basic disjoint information, for example, the point cloud. In this reconstruction, which can create watertight surfaces from project, we will use point clouds from FARO devices which oriented point sets. -
Point Cloud Subjective Evaluation Methodology Based on Reconstructed Surfaces
Point cloud subjective evaluation methodology based on reconstructed surfaces Evangelos Alexioua, Antonio M. G. Pinheirob, Carlos Duartec, Dragan Matkovi´cd, Emil Dumi´cd, Luis A. da Silva Cruzc, Lovorka Gotal Dmitrovi´cd, Marco V. Bernardob Manuela Pereirab and Touradj Ebrahimia aMultimedia Signal Processing Group, Ecole´ Polytechnique F´ed´eralede Lausanne, Switzerland; bInstitute of Telecommunications, University of Beira Interior, Portugal; cDepartment of Electrical and Computer Engineering, University of Coimbra and Institute of Telecommunications, Portugal; dDepartment of Electrical Engineering, University North, Croatia ABSTRACT Point clouds have been gaining importance as a solution to the problem of efficient representation of 3D geometric and visual information. They are commonly represented by large amounts of data, and compression schemes are important for their manipulation transmission and storing. However, the selection of appropriate compression schemes requires effective quality evaluation. In this work a subjective quality evaluation of point clouds using a surface representation is analyzed. Using a set of point cloud data objects encoded with the popular octree pruning method with different qualities, a subjective evaluation was designed. The point cloud geometry was presented to observers in the form of a movie showing the 3D Poisson reconstructed surface without textural information with the point of view changing in time. Subjective evaluations were performed in three different laboratories. Scores obtained from each test were correlated and no statistical differences were observed. Scores were also correlated with previous subjective tests and a good correlation was obtained when compared with mesh rendering in 2D monitors. Moreover, the results were correlated with state of the art point cloud objective metrics revealing poor correlation. -
MEPP2: a Generic Platform for Processing 3D Meshes and Point Clouds
EUROGRAPHICS 2020/ F. Banterle and A. Wilkie Short Paper MEPP2: a generic platform for processing 3D meshes and point clouds Vincent Vidal, Eric Lombardi , Martial Tola , Florent Dupont and Guillaume Lavoué Université de Lyon, CNRS, LIRIS, Lyon, France Abstract In this paper, we present MEPP2, an open-source C++ software development kit (SDK) for processing and visualizing 3D surface meshes and point clouds. It provides both an application programming interface (API) for creating new processing filters and a graphical user interface (GUI) that facilitates the integration of new filters as plugins. Static and dynamic 3D meshes and point clouds with appearance-related attributes (color, texture information, normal) are supported. The strength of the platform is to be generic programming oriented. It offers an abstraction layer, based on C++ Concepts, that provides interoperability over several third party mesh and point cloud data structures, such as OpenMesh, CGAL, and PCL. Generic code can be run on all data structures implementing the required concepts, which allows for performance and memory footprint comparison. Our platform also permits to create complex processing pipelines gathering idiosyncratic functionalities of the different libraries. We provide examples of such applications. MEPP2 runs on Windows, Linux & Mac OS X and is intended for engineers, researchers, but also students thanks to simple use, facilitated by the proposed architecture and extensive documentation. CCS Concepts • Computing methodologies ! Mesh models; Point-based models; • Software and its engineering ! Software libraries and repositories; 1. Introduction GUI for processing and visualizing 3D surface meshes and point clouds. With the increasing capability of 3D data acquisition devices, mod- Several platforms exist for processing 3D meshes such as Meshlab eling software and graphics processing units, three-dimensional [CCC08] based on VCGlibz, MEPP [LTD12], and libigl [JP∗18]. -
From Laser Scanner Point Clouds to 3D Modeling of the Valencian Silo-Yard in Burjassot”
Hochschule Karlsruhe – Technik und Wirtschaft University of Applied Sciences Fakultät für Fakultät für Informationsmanagement und Medien Master´s Programme Geomatics Master´s Thesis of María Cristina Gómez Peribáñez FROM LASER SCANNER POINT CLOUDS TO 3D MODELING OF THE VALENCIAN SILO-YARD IN BURJASSOT First Referee: Prof. Dr.-Ing. H. Saler Second Referee: Prof. Dr.-Ing. V. Tsioukas (AUTH) Third Referee: Prof. Dr.-Ing. F. Buchón (UPV) Karlsruhe, September 2017 Acknowledgement I would like to express my sincere thanks to all those who have made this Master Thesis possible, especially to the program Baden- Württemberg Stipendium. I would like to thank my tutors Heinz Saler, Vassilis Tsioukas and Fernando Buchón, for the time they have given me, for their help and support in this project. To my parents, family and friends, I would also like to thank you for your daily support to complete this project. Especially to Irini for all her help. Thanks. María Cristina Gómez Peribáñez I | P a g e Hochschule Karlsruhe – Technik und Wirtschaft Aristotle University of Thessaloniki -Faculty of Engineering University Polytechnic of Valencia Table of contents Acknowledgement ......................................................................................................................... I Table of contents .......................................................................................................................... 1 List of figures ............................................................................................................................... -
Choosing a Photogrammetry Workflow for Cultural Heritage Groups
heritage Article To 3D or Not 3D: Choosing a Photogrammetry Workflow for Cultural Heritage Groups Hafizur Rahaman * and Erik Champion School of Media, Creative Arts, and Social Inquiry, Curtin University, Perth, WA 6845, Australia * Correspondence: hafi[email protected]; Tel.: +61-8-9266-3339 Received: 22 May 2019; Accepted: 28 June 2019; Published: 3 July 2019 Abstract: The 3D reconstruction of real-world heritage objects using either a laser scanner or 3D modelling software is typically expensive and requires a high level of expertise. Image-based 3D modelling software, on the other hand, offers a cheaper alternative, which can handle this task with relative ease. There also exists free and open source (FOSS) software, with the potential to deliver quality data for heritage documentation purposes. However, contemporary academic discourse seldom presents survey-based feature lists or a critical inspection of potential production pipelines, nor typically provides direction and guidance for non-experts who are interested in learning, developing and sharing 3D content on a restricted budget. To address the above issues, a set of FOSS were studied based on their offered features, workflow, 3D processing time and accuracy. Two datasets have been used to compare and evaluate the FOSS applications based on the point clouds they produced. The average deviation to ground truth data produced by a commercial software application (Metashape, formerly called PhotoScan) was used and measured with CloudCompare software. 3D reconstructions generated from FOSS produce promising results, with significant accuracy, and are easy to use. We believe this investigation will help non-expert users to understand the photogrammetry and select the most suitable software for producing image-based 3D models at low cost for visualisation and presentation purposes.