Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
7.9
5.0
Journals
Remote Sensing
Special Issues
Remote Sensed Data and Processing Methodologies for 3D Virtual Reconstruction...
remotesensing-logo
Submit to Remote Sensing Review for Remote Sensing Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Remote Sensed Data and Processing Methodologies for 3D Virtual Reconstruction and Visualization of Complex Architectures

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (30 November 2015) | Viewed by 173507

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Prof. Dr. Diego González-Aguilera

E-Mail Website
Guest Editor
Cartographic and Land Engineering Department, Higher Polytechnic School of Avila, University of Salamanca, Hornos Caleros, 50, 05003 Avila, Spain
Interests: photogrammetry; laser scanning; 3D modeling; topography; cartography
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Fabio Remondino

E-Mail Website
Guest Editor
3D Optical Metrology (3DOM) Unit, Bruno Kessler Foundation (FBK), 38123 Trento, Italy
Interests: photogrammetry; laser scanning; optical metrology; 3D; AI; quality control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, the topic of 3D reconstruction and modeling of complex architectures from remotely acquired multiple data sources has been of growing interest. This “democratization” of 3D modeling processes and the large availability of data is, however, not always followed by reliable, affordable and powerful tools for realizing photo-realistic, metric, re-usable and semantic-aware 3D products. This should be a motivation to research, design, develop and validate novel easy-to-use, ease-to-learn and a low-cost framework for 3D modeling and further understanding of virtual environments using multiple data sources, so that the whole 3D modeling community has access to an affordable, transferable, functional and usable framework of methods and tools. This challenge causes several problems that should be addressed: from improving and testing the technical capabilities of new capturing devices, to the solution of problems resultant from large image blocks, from delivering Building Information Modeling (BIM) standards in order to provide new management approaches to replacing existing visualization tools with new working experiences such as Virtual and Augmented Reality or game-engine technology.

This Special Issue stems from from the ISPRS 3D-ARCH workshop series (http://3d-arch.org) and will accept improved and extended selected papers derived from the workshop proceedings, as well as new contributions from international colleagues.

We invite you to submit articles on the following topics:

  • Multi-source data and multi-sensors integration for advanced terrestrial 3D modeling
  • New low-cost sensors and open-source algorithms for terrestrial 3D modeling
  • Automation in data registration
  • Dense image matching and automated 3D reconstruction
  • Point cloud analysis and feature extraction
  • Novel methods for the generation of structured 3D data from unstructured point clouds
  • Procedural modeling and HBIM
  • Accuracy requirement and assessment in 3D reconstructions
  • Virtual and Augmented Reality applied to the visualization and conservation of complex architectures and heritage

Authors are required to check and follow specific Instructions to Authors, see https://dl.dropboxusercontent.com/u/165068305/Remote_Sensing-Additional_Instructions.pdf

Dr. Diego Gonzalez-Aguilera
Dr. Fabio Remondino
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (19 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Review, Other

5783 KiB  
Article
A Multi-View Dense Point Cloud Generation Algorithm Based on Low-Altitude Remote Sensing Images
by Zhenfeng Shao, Nan Yang, Xiongwu Xiao, Lei Zhang and Zhe Peng
Remote Sens. 2016, 8(5), 381; https://doi.org/10.3390/rs8050381 - 04 May 2016
Cited by 37 | Viewed by 7377
Abstract
This paper presents a novel multi-view dense point cloud generation algorithm based on low-altitude remote sensing images. The proposed method was designed to be especially effective in enhancing the density of point clouds generated by Multi-View Stereo (MVS) algorithms. To overcome the limitations [...] Read more.
This paper presents a novel multi-view dense point cloud generation algorithm based on low-altitude remote sensing images. The proposed method was designed to be especially effective in enhancing the density of point clouds generated by Multi-View Stereo (MVS) algorithms. To overcome the limitations of MVS and dense matching algorithms, an expanded patch was set up for each point in the point cloud. Then, a patch-based Multiphoto Geometrically Constrained Matching (MPGC) was employed to optimize points on the patch based on least square adjustment, the space geometry relationship, and epipolar line constraint. The major advantages of this approach are twofold: (1) compared with the MVS method, the proposed algorithm can achieve denser three-dimensional (3D) point cloud data; and (2) compared with the epipolar-based dense matching method, the proposed method utilizes redundant measurements to weaken the influence of occlusion and noise on matching results. Comparison studies and experimental results have validated the accuracy of the proposed algorithm in low-altitude remote sensing image dense point cloud generation. Full article
(This article belongs to the Special Issue Remote Sensed Data and Processing Methodologies for 3D Virtual Reconstruction and Visualization of Complex Architectures)
►▼ Show Figures

Graphical abstract

20017 KiB  
Article
Fine Surveying and 3D Modeling Approach for Wooden Ancient Architecture via Multiple Laser Scanner Integration
by Qingwu Hu, Shaohua Wang, Caiwu Fu, Mingyao Ai, Dengbo Yu and Wende Wang
Remote Sens. 2016, 8(4), 270; https://doi.org/10.3390/rs8040270 - 25 Mar 2016
Cited by 36 | Viewed by 9870
Abstract
A multiple terrestrial laser scanner (TLS) integration approach is proposed for the fine surveying and 3D modeling of ancient wooden architecture in an ancient building complex of Wudang Mountains, which is located in very steep surroundings making it difficult to access. Three-level TLS [...] Read more.
A multiple terrestrial laser scanner (TLS) integration approach is proposed for the fine surveying and 3D modeling of ancient wooden architecture in an ancient building complex of Wudang Mountains, which is located in very steep surroundings making it difficult to access. Three-level TLS with a scalable measurement distance and accuracy is presented for data collection to compensate for data missed because of mutual sheltering and scanning view limitations. A multi-scale data fusion approach is proposed for data registration and filtering of the different scales and separated 3D data. A point projection algorithm together with point cloud slice tools is designed for fine surveying to generate all types of architecture maps, such as plan drawings, facade drawings, section drawings, and doors and windows drawings. The section drawings together with slicing point cloud are presented for the deformation analysis of the building structure. Along with fine drawings and laser scanning data, the 3D models of the ancient architecture components are built for digital management and visualization. Results show that the proposed approach can achieve fine surveying and 3D documentation of the ancient architecture within 3 mm accuracy. In addition, the defects of scanning view and mutual sheltering can overcome to obtain the complete and exact structure in detail. Full article
(This article belongs to the Special Issue Remote Sensed Data and Processing Methodologies for 3D Virtual Reconstruction and Visualization of Complex Architectures)
►▼ Show Figures

Graphical abstract

13474 KiB  
Article
Frescoed Vaults: Accuracy Controlled Simplified Methodology for Planar Development of Three-Dimensional Textured Models
by Marco Giorgio Bevilacqua, Gabriella Caroti, Isabel Martínez-Espejo Zaragoza and Andrea Piemonte
Remote Sens. 2016, 8(3), 239; https://doi.org/10.3390/rs8030239 - 14 Mar 2016
Cited by 17 | Viewed by 6830
Abstract
In the field of documentation and preservation of cultural heritage, there is keen interest in 3D metric viewing and rendering of architecture for both formal appearance and color. On the other hand, operative steps of restoration interventions still require full-scale, 2D metric surface [...] Read more.
In the field of documentation and preservation of cultural heritage, there is keen interest in 3D metric viewing and rendering of architecture for both formal appearance and color. On the other hand, operative steps of restoration interventions still require full-scale, 2D metric surface representations. The transition from 3D to 2D representation, with the related geometric transformations, has not yet been fully formalized for planar development of frescoed vaults. Methodologies proposed so far on this subject provide transitioning from point cloud models to ideal mathematical surfaces and projecting textures using software tools. The methodology used for geometry and texture development in the present work does not require any dedicated software. The different processing steps can be individually checked for any error introduced, which can be then quantified. A direct accuracy check of the planar development of the frescoed surface has been carried out by qualified restorers, yielding a result of 3 mm. The proposed methodology, although requiring further studies to improve automation of the different processing steps, allowed extracting 2D drafts fully usable by operators restoring the vault frescoes. Full article
(This article belongs to the Special Issue Remote Sensed Data and Processing Methodologies for 3D Virtual Reconstruction and Visualization of Complex Architectures)
►▼ Show Figures

Graphical abstract

20919 KiB  
Article
An Advanced Pre-Processing Pipeline to Improve Automated Photogrammetric Reconstructions of Architectural Scenes
by Marco Gaiani, Fabio Remondino, Fabrizio I. Apollonio and Andrea Ballabeni
Remote Sens. 2016, 8(3), 178; https://doi.org/10.3390/rs8030178 - 25 Feb 2016
Cited by 54 | Viewed by 13628
Abstract
Automated image-based 3D reconstruction methods are more and more flooding our 3D modeling applications. Fully automated solutions give the impression that from a sample of randomly acquired images we can derive quite impressive visual 3D models. Although the level of automation is reaching [...] Read more.
Automated image-based 3D reconstruction methods are more and more flooding our 3D modeling applications. Fully automated solutions give the impression that from a sample of randomly acquired images we can derive quite impressive visual 3D models. Although the level of automation is reaching very high standards, image quality is a fundamental pre-requisite to produce successful and photo-realistic 3D products, in particular when dealing with large datasets of images. This article presents an efficient pipeline based on color enhancement, image denoising, color-to-gray conversion and image content enrichment. The pipeline stems from an analysis of various state-of-the-art algorithms and aims to adjust the most promising methods, giving solutions to typical failure causes. The assessment evaluation proves how an effective image pre-processing, which considers the entire image dataset, can improve the automated orientation procedure and dense 3D point cloud reconstruction, even in the case of poor texture scenarios. Full article
(This article belongs to the Special Issue Remote Sensed Data and Processing Methodologies for 3D Virtual Reconstruction and Visualization of Complex Architectures)
►▼ Show Figures

Graphical abstract

4495 KiB  
Article
Multi-Class Simultaneous Adaptive Segmentation and Quality Control of Point Cloud Data
by Ayman Habib and Yun-Jou Lin
Remote Sens. 2016, 8(2), 104; https://doi.org/10.3390/rs8020104 - 29 Jan 2016
Cited by 28 | Viewed by 6226
Abstract
3D modeling of a given site is an important activity for a wide range of applications including urban planning, as-built mapping of industrial sites, heritage documentation, military simulation, and outdoor/indoor analysis of airflow. Point clouds, which could be either derived from passive or [...] Read more.
3D modeling of a given site is an important activity for a wide range of applications including urban planning, as-built mapping of industrial sites, heritage documentation, military simulation, and outdoor/indoor analysis of airflow. Point clouds, which could be either derived from passive or active imaging systems, are an important source for 3D modeling. Such point clouds need to undergo a sequence of data processing steps to derive the necessary information for the 3D modeling process. Segmentation is usually the first step in the data processing chain. This paper presents a region-growing multi-class simultaneous segmentation procedure, where planar, pole-like, and rough regions are identified while considering the internal characteristics (i.e., local point density/spacing and noise level) of the point cloud in question. The segmentation starts with point cloud organization into a kd-tree data structure and characterization process to estimate the local point density/spacing. Then, proceeding from randomly-distributed seed points, a set of seed regions is derived through distance-based region growing, which is followed by modeling of such seed regions into planar and pole-like features. Starting from optimally-selected seed regions, planar and pole-like features are then segmented. The paper also introduces a list of hypothesized artifacts/problems that might take place during the region-growing process. Finally, a quality control process is devised to detect, quantify, and mitigate instances of partially/fully misclassified planar and pole-like features. Experimental results from airborne and terrestrial laser scanning as well as image-based point clouds are presented to illustrate the performance of the proposed segmentation and quality control framework. Full article
(This article belongs to the Special Issue Remote Sensed Data and Processing Methodologies for 3D Virtual Reconstruction and Visualization of Complex Architectures)
►▼ Show Figures

Graphical abstract

19213 KiB  
Article
Multi-View Stereo Matching Based on Self-Adaptive Patch and Image Grouping for Multiple Unmanned Aerial Vehicle Imagery
by Xiongwu Xiao, Bingxuan Guo, Deren Li, Linhui Li, Nan Yang, Jianchen Liu, Peng Zhang and Zhe Peng
Remote Sens. 2016, 8(2), 89; https://doi.org/10.3390/rs8020089 - 23 Jan 2016
Cited by 35 | Viewed by 8114
Abstract
Robust and rapid image dense matching is the key to large-scale three-dimensional (3D) reconstruction for multiple Unmanned Aerial Vehicle (UAV) images. However, the following problems must be addressed: (1) the amount of UAV image data is very large, but ordinary computer memory is [...] Read more.
Robust and rapid image dense matching is the key to large-scale three-dimensional (3D) reconstruction for multiple Unmanned Aerial Vehicle (UAV) images. However, the following problems must be addressed: (1) the amount of UAV image data is very large, but ordinary computer memory is limited; (2) the patch-based multi-view stereo-matching algorithm (PMVS) does not work well for narrow-baseline cases, and its computing efficiency is relatively low, and thus, it is difficult to meet the UAV photogrammetry’s requirements of convenience and speed. This paper proposes an Image-grouping and Self-Adaptive Patch-based Multi-View Stereo-matching algorithm (IG-SAPMVS) for multiple UAV imagery. First, multiple UAV images were grouped reasonably by a certain grouping strategy. Second, image dense matching was performed in each group and included three processes. (1) Initial feature-matching consists of two steps: The first was feature point detection and matching, which made some improvements to PMVS, according to the characteristics of UAV imagery. The second was edge point detection and matching, which aimed to control matching propagation during the expansion process; (2) The second process was matching propagation based on the self-adaptive patch. Initial patches were built that were centered by the obtained 3D seed points, and these were repeatedly expanded. The patches were prevented from crossing the discontinuous terrain by using the edge constraint, and the extent size and shape of the patches could automatically adapt to the terrain relief; (3) The third process was filtering the erroneous matching points. Taken the overlap problem between each group of 3D dense point clouds into account, the matching results were merged into a whole. Experiments conducted on three sets of typical UAV images with different texture features demonstrate that the proposed algorithm can address a large amount of UAV image data almost without computer memory restrictions, and the processing efficiency is significantly better than that of the PMVS algorithm and the matching accuracy is equal to that of the state-of-the-art PMVS algorithm. Full article
(This article belongs to the Special Issue Remote Sensed Data and Processing Methodologies for 3D Virtual Reconstruction and Visualization of Complex Architectures)
►▼ Show Figures

Graphical abstract

7259 KiB  
Article
Multispectral Radiometric Analysis of Façades to Detect Pathologies from Active and Passive Remote Sensing
by Susana Del Pozo, Jesús Herrero-Pascual, Beatriz Felipe-García, David Hernández-López, Pablo Rodríguez-Gonzálvez and Diego González-Aguilera
Remote Sens. 2016, 8(1), 80; https://doi.org/10.3390/rs8010080 - 21 Jan 2016
Cited by 42 | Viewed by 7857
Abstract
This paper presents a radiometric study to recognize pathologies in façades of historical buildings by using two different remote sensing technologies covering part of the visible and very near infrared spectrum (530–905 nm). Building materials deteriorate over the years due to different extrinsic [...] Read more.
This paper presents a radiometric study to recognize pathologies in façades of historical buildings by using two different remote sensing technologies covering part of the visible and very near infrared spectrum (530–905 nm). Building materials deteriorate over the years due to different extrinsic and intrinsic agents, so assessing these affections in a non-invasive way is crucial to help preserve them since in many cases they are valuable and some have been declared monuments of cultural interest. For the investigation, passive and active remote acquisition systems were applied operating at different wavelengths. A 6-band Mini-MCA multispectral camera (530–801 nm) and a FARO Focus3D terrestrial laser scanner (905 nm) were used with the dual purpose of detecting different materials and damages on building façades as well as determining which acquisition system and spectral range is more suitable for this kind of studies. The laser scan points were used as base to create orthoimages, the input of the two different classification processes performed. The set of all orthoimages from both sensors was classified under supervision. Furthermore, orthoimages from each individual sensor were automatically classified to compare results from each sensor with the reference supervised classification. Higher overall accuracy with the FARO Focus3D, 74.39%, was obtained with respect to the Mini MCA6, 66.04%. Finally, after applying the radiometric calibration, a minimum improvement of 24% in the image classification results was obtained in terms of overall accuracy. Full article
(This article belongs to the Special Issue Remote Sensed Data and Processing Methodologies for 3D Virtual Reconstruction and Visualization of Complex Architectures)
►▼ Show Figures

Graphical abstract

5924 KiB  
Article
Photogrammetric, Geometrical, and Numerical Strategies to Evaluate Initial and Current Conditions in Historical Constructions: A Test Case in the Church of San Lorenzo (Zamora, Spain)
by Luis Javier Sánchez-Aparicio, Alberto Villarino, Jesús García-Gago and Diego González-Aguilera
Remote Sens. 2016, 8(1), 60; https://doi.org/10.3390/rs8010060 - 13 Jan 2016
Cited by 21 | Viewed by 6566
Abstract
Identifying and quantifying the potential causes of damages to a construction and evaluating its current stability have become an imperative task in today’s world. However, the existence of variables, unknown conditions and a complex geometry hinder such work, by hampering the numerical results [...] Read more.
Identifying and quantifying the potential causes of damages to a construction and evaluating its current stability have become an imperative task in today’s world. However, the existence of variables, unknown conditions and a complex geometry hinder such work, by hampering the numerical results that simulate its behavior. Of the mentioned variables, the following can be highlighted: (i) the lack of historical information; (ii) the mechanical properties of the material; (iii) the initial geometry and (iv) the interaction with other structures. Within the field of remote sensors, the laser scanner and photogrammetric systems have become especially valuable for construction analysis. Such sensors are capable of providing highly accurate and dense geometrical data with which to assess a building’s condition. It is also remarkable, that the latter provide valuable radiometric data with which to identify the properties of the materials, and also evaluate and monitor crack patterns. Motivated by this, the present article investigates the potential offered by the combined use of photogrammetric techniques (DIC and SfM), as well as geometrical (NURBs and Hausdorff distance) and numerical strategies (FEM) to assess the origin of the damage (through an estimation of the initial conditions) and give an evaluation of the current stability (considering the deformation and the damage). Full article
(This article belongs to the Special Issue Remote Sensed Data and Processing Methodologies for 3D Virtual Reconstruction and Visualization of Complex Architectures)
►▼ Show Figures

Graphical abstract

10494 KiB  
Article
A New Approach to the Generation of Orthoimages of Cultural Heritage Objects—Integrating TLS and Image Data
by Jakub Stefan Markiewicz, Piotr Podlasiak and Dorota Zawieska
Remote Sens. 2015, 7(12), 16963-16985; https://doi.org/10.3390/rs71215869 - 16 Dec 2015
Cited by 24 | Viewed by 6730
Abstract
This paper discusses the issue of automation of orthoimage generation based on Terrestrial Laser Scanning (TLS) data and digital images. The following two problems are discussed: automatic generation of projection planes based on TLS data, and automatic orientation of digital images in relation [...] Read more.
This paper discusses the issue of automation of orthoimage generation based on Terrestrial Laser Scanning (TLS) data and digital images. The following two problems are discussed: automatic generation of projection planes based on TLS data, and automatic orientation of digital images in relation to TLS data. The majority of popular software applications use manual definitions of projection planes. However, the authors propose an original software tool to address the first issue, which defines important planes based on a TLS point cloud utilizing different algorithms (RANdom SAmple Consensus–RANSAC, Hough transform, “region growing”). To address the second task, the authors present a series of algorithms for automated digital image orientation in relation to a point cloud. This is important in cases where scans and images are acquired from different places and at different times. The algorithms utilize Scale Invariant Feature Transform(SIFT) operators in order to find points that correspond in reflectance intensity between coloure images (Red Green Blue—RGB) and orthoimages, based on TLS data. The paper also presents a verification method using SIFT and Speeded-Up Robust Features (SURF) operators. The research results in an original tool and applied Computer Vision(CV) algorithms that improve the process of orthoimage generation. Full article
(This article belongs to the Special Issue Remote Sensed Data and Processing Methodologies for 3D Virtual Reconstruction and Visualization of Complex Architectures)
►▼ Show Figures

Graphical abstract

9805 KiB  
Article
Multi-Sensor As-Built Models of Complex Industrial Architectures
by Jean-François Hullo, Guillaume Thibault, Christian Boucheny, Fabien Dory and Arnaud Mas
Remote Sens. 2015, 7(12), 16339-16362; https://doi.org/10.3390/rs71215827 - 04 Dec 2015
Cited by 29 | Viewed by 6895
Abstract
In the context of increased maintenance operations and generational renewal work, a nuclear owner and operator, like Electricité de France (EDF), is invested in the scaling-up of tools and methods of “as-built virtual reality” for whole buildings and large audiences. In this paper, [...] Read more.
In the context of increased maintenance operations and generational renewal work, a nuclear owner and operator, like Electricité de France (EDF), is invested in the scaling-up of tools and methods of “as-built virtual reality” for whole buildings and large audiences. In this paper, we first present the state of the art of scanning tools and methods used to represent a very complex architecture. Then, we propose a methodology and assess it in a large experiment carried out on the most complex building of a 1300-megawatt power plant, an 11-floor reactor building. We also present several developments that made possible the acquisition, processing and georeferencing of multiple data sources (1000+ 3D laser scans and RGB panoramic, total-station surveying, 2D floor plans and the 3D reconstruction of CAD as-built models). In addition, we introduce new concepts for user interaction with complex architecture, elaborated during the development of an application that allows a painless exploration of the whole dataset by professionals, unfamiliar with such data types. Finally, we discuss the main feedback items from this large experiment, the remaining issues for the generalization of such large-scale surveys and the future technical and scientific challenges in the field of industrial “virtual reality”. Full article
(This article belongs to the Special Issue Remote Sensed Data and Processing Methodologies for 3D Virtual Reconstruction and Visualization of Complex Architectures)
►▼ Show Figures

Graphical abstract

1379 KiB  
Article
Data Product Specification Proposal for Architectural Heritage Documentation with Photogrammetric Techniques: A Case Study in Brazil
by Mariana B. Campos, Antonio M. G. Tommaselli, Ivana Ivánová and Roland Billen
Remote Sens. 2015, 7(10), 13337-13363; https://doi.org/10.3390/rs71013337 - 12 Oct 2015
Cited by 13 | Viewed by 5886
Abstract
Photogrammetric documentation can provide a sound database for the needs of architectural heritage preservation. However, the major part of photogrammetric documentation production is not used for subsequent architectural heritage projects, due to lack of knowledge of photogrammetric documentation accuracy. In addition, there are [...] Read more.
Photogrammetric documentation can provide a sound database for the needs of architectural heritage preservation. However, the major part of photogrammetric documentation production is not used for subsequent architectural heritage projects, due to lack of knowledge of photogrammetric documentation accuracy. In addition, there are only a few studies with rigorous analysis of the requirements for photogrammetric documentation of architectural heritage. In particular, requirements focusing on the geometry of the models generated by fully digital photogrammetric processes are missing. Considering these needs, this paper presents a procedure for architectural heritage documentation with photogrammetric techniques based on a previous review of existing standards of architectural heritage documentation. The data product specification proposed was elaborated conforming to ISO 19131 recommendations. We present the procedure with two case studies in the context of Brazilian architectural heritage documentation. Quality analysis of the produced models were performed considering ISO 19157 elements, such as positional accuracy, logical consistency and completeness, meeting the requirements. Our results confirm that the proposed requirements for photogrammetric documentation are viable. Full article
(This article belongs to the Special Issue Remote Sensed Data and Processing Methodologies for 3D Virtual Reconstruction and Visualization of Complex Architectures)
►▼ Show Figures

Graphical abstract

5593 KiB  
Article
Assessment and Calibration of a RGB-D Camera (Kinect v2 Sensor) Towards a Potential Use for Close-Range 3D Modeling
by Elise Lachat, Hélène Macher, Tania Landes and Pierre Grussenmeyer
Remote Sens. 2015, 7(10), 13070-13097; https://doi.org/10.3390/rs71013070 - 01 Oct 2015
Cited by 179 | Viewed by 16533
Abstract
In the last decade, RGB-D cameras - also called range imaging cameras - have known a permanent evolution. Because of their limited cost and their ability to measure distances at a high frame rate, such sensors are especially appreciated for applications in robotics [...] Read more.
In the last decade, RGB-D cameras - also called range imaging cameras - have known a permanent evolution. Because of their limited cost and their ability to measure distances at a high frame rate, such sensors are especially appreciated for applications in robotics or computer vision. The Kinect v1 (Microsoft) release in November 2010 promoted the use of RGB-D cameras, so that a second version of the sensor arrived on the market in July 2014. Since it is possible to obtain point clouds of an observed scene with a high frequency, one could imagine applying this type of sensors to answer to the need for 3D acquisition. However, due to the technology involved, some questions have to be considered such as, for example, the suitability and accuracy of RGB-D cameras for close range 3D modeling. In that way, the quality of the acquired data represents a major axis. In this paper, the use of a recent Kinect v2 sensor to reconstruct small objects in three dimensions has been investigated. To achieve this goal, a survey of the sensor characteristics as well as a calibration approach are relevant. After an accuracy assessment of the produced models, the benefits and drawbacks of Kinect v2 compared to the first version of the sensor and then to photogrammetry are discussed. Full article
(This article belongs to the Special Issue Remote Sensed Data and Processing Methodologies for 3D Virtual Reconstruction and Visualization of Complex Architectures)
►▼ Show Figures

Graphical abstract

1332 KiB  
Article
Automatic Geometry Generation from Point Clouds for BIM
by Charles Thomson and Jan Boehm
Remote Sens. 2015, 7(9), 11753-11775; https://doi.org/10.3390/rs70911753 - 14 Sep 2015
Cited by 165 | Viewed by 15375
Abstract
The need for better 3D documentation of the built environment has come to the fore in recent years, led primarily by city modelling at the large scale and Building Information Modelling (BIM) at the smaller scale. Automation is seen as desirable as it [...] Read more.
The need for better 3D documentation of the built environment has come to the fore in recent years, led primarily by city modelling at the large scale and Building Information Modelling (BIM) at the smaller scale. Automation is seen as desirable as it removes the time-consuming and therefore costly amount of human intervention in the process of model generation. BIM is the focus of this paper as not only is there a commercial need, as will be shown by the number of commercial solutions, but also wide research interest due to the aspiration of automated 3D models from both Geomatics and Computer Science communities. The aim is to go beyond the current labour-intensive tracing of the point cloud to an automated process that produces geometry that is both open and more verifiable. This work investigates what can be achieved today with automation through both literature review and by proposing a novel point cloud processing process. We present an automated workflow for the generation of BIM data from 3D point clouds. We also present quality indicators for reconstructed geometry elements and a framework in which to assess the quality of the reconstructed geometry against a reference. Full article
(This article belongs to the Special Issue Remote Sensed Data and Processing Methodologies for 3D Virtual Reconstruction and Visualization of Complex Architectures)
►▼ Show Figures

Graphical abstract

808 KiB  
Article
Geometrical Issues on the Structural Analysis of Transmission Electricity Towers Thanks to Laser Scanning Technology and Finite Element Method
by Borja Conde, Alberto Villarino, Manuel Cabaleiro and Diego Gonzalez-Aguilera
Remote Sens. 2015, 7(9), 11551-11569; https://doi.org/10.3390/rs70911551 - 10 Sep 2015
Cited by 18 | Viewed by 11782
Abstract
This paper presents a multidisciplinary approach to reverse engineering and structural analysis of electricity transmission tower structures through the combination of laser scanning systems and finite element methodology. The use of laser scanning technology allows the development of both drawings and highly accurate [...] Read more.
This paper presents a multidisciplinary approach to reverse engineering and structural analysis of electricity transmission tower structures through the combination of laser scanning systems and finite element methodology. The use of laser scanning technology allows the development of both drawings and highly accurate three-dimensional geometric models that reliably reproduce geometric reality of towers structures, detecting imperfections, and particularities of their assembly. Due to this, it is possible to analyze and quantify the effect of these imperfections in their structural behavior, taking into account the actual geometry obtained, different structural models, and load hypotheses proposed. The method has been applied in three different types of metal electricity transmission towers with high voltage lines located in Guadalajara (Spain) in order to analyze its structural viability to accommodate future increased loads with respect that which are currently subjected. Full article
(This article belongs to the Special Issue Remote Sensed Data and Processing Methodologies for 3D Virtual Reconstruction and Visualization of Complex Architectures)
►▼ Show Figures

Graphical abstract

3275 KiB  
Article
Scanning Photogrammetry for Measuring Large Targets in Close Range
by Shan Huang, Zuxun Zhang, Tao Ke, Min Tang and Xuan Xu
Remote Sens. 2015, 7(8), 10042-10077; https://doi.org/10.3390/rs70810042 - 07 Aug 2015
Cited by 12 | Viewed by 8713
Abstract
In close-range photogrammetry, images are difficult to acquire and organize primarily because of the limited field of view (FOV) of digital cameras when long focal lenses are used to measure large targets. To overcome this problem, we apply a scanning photography method that [...] Read more.
In close-range photogrammetry, images are difficult to acquire and organize primarily because of the limited field of view (FOV) of digital cameras when long focal lenses are used to measure large targets. To overcome this problem, we apply a scanning photography method that acquires images by rotating the camera in both horizontal and vertical directions at one station. This approach not only enlarges the FOV of each station but also ensures that all stations are distributed in order without coverage gap. We also conduct a modified triangulation according to the traits of the data overlapping among images from the same station to avoid matching all images with one another. This algorithm synthesizes the images acquired from the same station into synthetic images, which are then used to generate a free network. Consequently, we solve the exterior orientation elements of each original camera image in the free network and perform image matching among original images to obtain tie points. Finally, all original images are combined in self-calibration bundle adjustment with control points. The feasibility and precision of the proposed method are validated by testing it on two fields using 300 and 600 mm lenses. The results confirm that even with a small amount of control points, the developed scanning photogrammetry can steadily achieve millimeter scale accuracy at distances ranging from 40 m to 250 m. Full article
(This article belongs to the Special Issue Remote Sensed Data and Processing Methodologies for 3D Virtual Reconstruction and Visualization of Complex Architectures)
►▼ Show Figures

Graphical abstract

12786 KiB  
Article
Optimized 3D Street Scene Reconstruction from Driving Recorder Images
by Yongjun Zhang, Qian Li, Hongshu Lu, Xinyi Liu, Xu Huang, Chao Song, Shan Huang and Jingyi Huang
Remote Sens. 2015, 7(7), 9091-9121; https://doi.org/10.3390/rs70709091 - 17 Jul 2015
Cited by 13 | Viewed by 8018
Abstract
The paper presents an automatic region detection based method to reconstruct street scenes from driving recorder images. The driving recorder in this paper is a dashboard camera that collects images while the motor vehicle is moving. An enormous number of moving vehicles are [...] Read more.
The paper presents an automatic region detection based method to reconstruct street scenes from driving recorder images. The driving recorder in this paper is a dashboard camera that collects images while the motor vehicle is moving. An enormous number of moving vehicles are included in the collected data because the typical recorders are often mounted in the front of moving vehicles and face the forward direction, which can make matching points on vehicles and guardrails unreliable. Believing that utilizing these image data can reduce street scene reconstruction and updating costs because of their low price, wide use, and extensive shooting coverage, we therefore proposed a new method, which is called the Mask automatic detecting method, to improve the structure results from the motion reconstruction. Note that we define vehicle and guardrail regions as “mask” in this paper since the features on them should be masked out to avoid poor matches. After removing the feature points in our new method, the camera poses and sparse 3D points that are reconstructed with the remaining matches. Our contrast experiments with the typical pipeline of structure from motion (SfM) reconstruction methods, such as Photosynth and VisualSFM, demonstrated that the Mask decreased the root-mean-square error (RMSE) of the pairwise matching results, which led to more accurate recovering results from the camera-relative poses. Removing features from the Mask also increased the accuracy of point clouds by nearly 30%–40% and corrected the problems of the typical methods on repeatedly reconstructing several buildings when there was only one target building. Full article
(This article belongs to the Special Issue Remote Sensed Data and Processing Methodologies for 3D Virtual Reconstruction and Visualization of Complex Architectures)
►▼ Show Figures

Graphical abstract

Review

Jump to: Research, Other

9041 KiB  
Review
A Survey of Algorithmic Shapes
by Ulrich Krispel, Christoph Schinko and Torsten Ullrich
Remote Sens. 2015, 7(10), 12763-12792; https://doi.org/10.3390/rs71012763 - 28 Sep 2015
Cited by 8 | Viewed by 10197
Abstract
In the context of computer-aided design, computer graphics and geometry processing, the idea of generative modeling is to allow the generation of highly complex objects based on a set of formal construction rules. Using these construction rules, a shape is described by a [...] Read more.
In the context of computer-aided design, computer graphics and geometry processing, the idea of generative modeling is to allow the generation of highly complex objects based on a set of formal construction rules. Using these construction rules, a shape is described by a sequence of processing steps, rather than just by the result of all applied operations: shape design becomes rule design. Due to its very general nature, this approach can be applied to any domain and to any shape representation that provides a set of generating functions. The aim of this survey is to give an overview of the concepts and techniques of procedural and generative modeling, as well as their applications with a special focus on archeology and architecture. Full article
(This article belongs to the Special Issue Remote Sensed Data and Processing Methodologies for 3D Virtual Reconstruction and Visualization of Complex Architectures)
►▼ Show Figures

Graphical abstract

Other

Jump to: Research, Review

7801 KiB  
Technical Note
A Multi-Data Source and Multi-Sensor Approach for the 3D Reconstruction and Web Visualization of a Complex Archaelogical Site: The Case Study of “Tolmo De Minateda”
by Jose Alberto Torres-Martínez, Marcello Seddaiu, Pablo Rodríguez-Gonzálvez, David Hernández-López and Diego González-Aguilera
Remote Sens. 2016, 8(7), 550; https://doi.org/10.3390/rs8070550 - 29 Jun 2016
Cited by 27 | Viewed by 6855
Abstract
The complexity of archaeological sites hinders creation of an integral model using the current Geomatic techniques (i.e., aerial, close-range photogrammetry and terrestrial laser scanner) individually. A multi-sensor approach is therefore proposed as the optimal solution to provide a 3D reconstruction and visualization of [...] Read more.
The complexity of archaeological sites hinders creation of an integral model using the current Geomatic techniques (i.e., aerial, close-range photogrammetry and terrestrial laser scanner) individually. A multi-sensor approach is therefore proposed as the optimal solution to provide a 3D reconstruction and visualization of these complex sites. Sensor registration represents a riveting milestone when automation is required and when aerial and terrestrial datasets must be integrated. To this end, several problems must be solved: coordinate system definition, geo-referencing, co-registration of point clouds, geometric and radiometric homogeneity, etc. The proposed multi-data source and multi-sensor approach is applied to the study case of the “Tolmo de Minateda” archaeological site. A total extension of 9 ha is reconstructed, with an adapted level of detail, by an ultralight aerial platform (paratrike), an unmanned aerial vehicle, a terrestrial laser scanner and terrestrial photogrammetry. Finally, a mobile device (e.g., tablet or smartphone) has been used to integrate, optimize and visualize all this information, providing added value to archaeologists and heritage managers who want to use an efficient tool for their works at the site, and even for non-expert users who just want to know more about the archaeological settlement. Full article
(This article belongs to the Special Issue Remote Sensed Data and Processing Methodologies for 3D Virtual Reconstruction and Visualization of Complex Architectures)
►▼ Show Figures

Graphical abstract

5260 KiB  
Technical Note
Large Scale Automatic Analysis and Classification of Roof Surfaces for the Installation of Solar Panels Using a Multi-Sensor Aerial Platform
by Luis López-Fernández, Susana Lagüela, Inmaculada Picón and Diego González-Aguilera
Remote Sens. 2015, 7(9), 11226-11248; https://doi.org/10.3390/rs70911226 - 01 Sep 2015
Cited by 14 | Viewed by 7989
Abstract
A low-cost multi-sensor aerial platform, aerial trike, equipped with visible and thermographic sensors is used for the acquisition of all the data needed for the automatic analysis and classification of roof surfaces regarding their suitability to harbor solar panels. The geometry of a [...] Read more.
A low-cost multi-sensor aerial platform, aerial trike, equipped with visible and thermographic sensors is used for the acquisition of all the data needed for the automatic analysis and classification of roof surfaces regarding their suitability to harbor solar panels. The geometry of a georeferenced 3D point cloud generated from visible images using photogrammetric and computer vision algorithms, and the temperatures measured on thermographic images are decisive to evaluate the areas, tilts, orientations and the existence of obstacles to locate the optimal zones inside each roof surface for the installation of solar panels. This information is complemented with the estimation of the solar irradiation received by each surface. This way, large areas may be efficiently analyzed obtaining as final result the optimal locations for the placement of solar panels as well as the information necessary (location, orientation, tilt, area and solar irradiation) to estimate the productivity of a solar panel from its technical characteristics. Full article
(This article belongs to the Special Issue Remote Sensed Data and Processing Methodologies for 3D Virtual Reconstruction and Visualization of Complex Architectures)
►▼ Show Figures

Graphical abstract

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-19
Back to TopTop