scholarly journals 3D DOCUMENTATION OF 40 KILOMETERS OF HISTORICAL PORTICOES – THE CHALLENGE

2016 ◽  
Vol XLI-B5 ◽  
pp. 711-718 ◽  
Author(s):  
F. Remondino ◽  
M. Gaiani ◽  
F. Apollonio ◽  
A. Ballabeni ◽  
M. Ballabeni ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
Point Clouds ◽  
Level Of Detail ◽  
Digital Products ◽  
3D Documentation ◽  
Colored Point ◽  
Terrestrial Photogrammetry ◽  
The Web ◽  
Open Issues ◽  
Image Datasets

In the last years the image-based pipeline for 3D reconstruction purposes has received large interest leading to fully automated methodologies able to process large image datasets and deliver 3D products with a level of detail and precision variable according to the applications. Different open issues still exist, in particular when dealing with the 3D surveying and modeling of large and complex scenarios, like historical porticoes. The paper presents an evaluation of various surveying methods for the geometric documentation of ca 40km of historical porticoes in Bologna (Italy). Finally, terrestrial photogrammetry was chosen as the most flexible and productive technique in order to deliver 3D results in form of colored point clouds or textured 3D meshes accessible on the web. The presented digital products are a complementary material for the final candidature of the porticoes as UNESCO WHS.

scholarly journals 3D DOCUMENTATION OF 40 KILOMETERS OF HISTORICAL PORTICOES – THE CHALLENGE

2016 ◽  
Vol XLI-B5 ◽  
pp. 711-718 ◽  
Author(s):  
F. Remondino ◽  
M. Gaiani ◽  
F. Apollonio ◽  
A. Ballabeni ◽  
M. Ballabeni ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
Point Clouds ◽  
Level Of Detail ◽  
Digital Products ◽  
3D Documentation ◽  
Colored Point ◽  
Terrestrial Photogrammetry ◽  
The Web ◽  
Open Issues ◽  
Image Datasets

In the last years the image-based pipeline for 3D reconstruction purposes has received large interest leading to fully automated methodologies able to process large image datasets and deliver 3D products with a level of detail and precision variable according to the applications. Different open issues still exist, in particular when dealing with the 3D surveying and modeling of large and complex scenarios, like historical porticoes. The paper presents an evaluation of various surveying methods for the geometric documentation of ca 40km of historical porticoes in Bologna (Italy). Finally, terrestrial photogrammetry was chosen as the most flexible and productive technique in order to deliver 3D results in form of colored point clouds or textured 3D meshes accessible on the web. The presented digital products are a complementary material for the final candidature of the porticoes as UNESCO WHS.

scholarly journals A LOW-COST PANORAMIC CAMERA FOR THE 3D DOCUMENTATION OF CONTAMINATED CRIME SCENES

2017 ◽  
Vol XLII-2/W8 ◽  
pp. 1-8
Author(s):  
D. Abate ◽  
I. Toschi ◽  
C. Sturdy-Colls ◽  
F. Remondino
Keyword(s):  
3D Reconstruction ◽  
Low Cost ◽  
Point Clouds ◽  
Crime Scene ◽  
Data Registration ◽  
3D Point Clouds ◽  
3D Geometry ◽  
Before And After ◽  
Feature Based ◽  
3D Documentation

Crime scene documentation is a fundamental task which has to be undertaken in a fast, accurate and reliable way, highlighting evidence which can be further used for ensuring justice for victims and for guaranteeing the successful prosecution of perpetrators. The main focus of this paper is on the documentation of a typical crime scene and on the rapid recording of any possible contamination that could have influenced its original appearance. A 3D reconstruction of the environment is first generated by processing panoramas acquired with the low-cost Ricoh Theta 360 camera, and further analysed to highlight potentials and limits of this emerging and consumer-grade technology. Then, a methodology is proposed for the rapid recording of changes occurring between the original and the contaminated crime scene. The approach is based on an automatic 3D feature-based data registration, followed by a cloud-to-cloud distance computation, given as input the 3D point clouds generated before and after e.g. the misplacement of evidence. All the algorithms adopted for panoramas pre-processing, photogrammetric 3D reconstruction, 3D geometry registration and analysis, are presented and currently available in open-source or low-cost software solutions.

scholarly journals VISUALIZATION OF POINT CLOUD MODELS IN MOBILE AUGMENTED REALITY USING CONTINUOUS LEVEL OF DETAIL METHOD

2020 ◽  
Vol XLIV-4/W1-2020 ◽  
pp. 167-170
Author(s):  
L. Zhang ◽  
P. van Oosterom ◽  
H. Liu
Keyword(s):  
Augmented Reality ◽  
Point Cloud ◽  
Cloud Model ◽  
Point Clouds ◽  
Level Of Detail ◽  
Mobile Augmented Reality ◽  
Cloud Models ◽  
Point Cloud Model ◽  
Visual Artifacts ◽  
Mobile Ar

Abstract. Point clouds have become one of the most popular sources of data in geospatial fields due to their availability and flexibility. However, because of the large amount of data and the limited resources of mobile devices, the use of point clouds in mobile Augmented Reality applications is still quite limited. Many current mobile AR applications of point clouds lack fluent interactions with users. In our paper, a cLoD (continuous level-of-detail) method is introduced to filter the number of points to be rendered considerably, together with an adaptive point size rendering strategy, thus improve the rendering performance and remove visual artifacts of mobile AR point cloud applications. Our method uses a cLoD model that has an ideal distribution over LoDs, with which can remove unnecessary points without sudden changes in density as present in the commonly used discrete level-of-detail approaches. Besides, camera position, orientation and distance from the camera to point cloud model is taken into consideration as well. With our method, good interactive visualization of point clouds can be realized in the mobile AR environment, with both nice visual quality and proper resource consumption.

scholarly journals MODELLING LANDSCAPE MORPHODYNAMICS BY TERRESTRIAL PHOTOGRAMMETRY: AN APPLICATION TO BEACH AND FLUVIAL SYSTEMS

2016 ◽  
Vol XLI-B8 ◽  
pp. 1175-1182 ◽  
Author(s):  
E. Sánchez-García ◽  
A. Balaguer-Beser ◽  
R. Taborda ◽  
J. E. Pardo-Pascual
Keyword(s):  
Morphological Changes ◽  
Spatial Scales ◽  
Cost Effective ◽  
Point Clouds ◽  
Field Work ◽  
Fluvial Systems ◽  
Natural Systems ◽  
3D Point Clouds ◽  
Pilot Channel ◽  
Terrestrial Photogrammetry

Beach and fluvial systems are highly dynamic environments, being constantly modified by the action of different natural and anthropic phenomena. To understand their behaviour and to support a sustainable management of these fragile environments, it is very important to have access to cost-effective tools. These methods should be supported on cutting-edge technologies that allow monitoring the dynamics of the natural systems with high periodicity and repeatability at different temporal and spatial scales instead the tedious and expensive field-work that has been carried out up to date. The work herein presented analyses the potential of terrestrial photogrammetry to describe beach morphology. Data processing and generation of high resolution 3D point clouds and derived DEMs is supported by the commercial Agisoft PhotoScan. Model validation is done by comparison of the differences in the elevation among the photogrammetric point cloud and the GPS data along different beach profiles. Results obtained denote the potential that the photogrammetry 3D modelling has to monitor morphological changes and natural events getting differences between 6 and 25 cm. Furthermore, the usefulness of these techniques to control the layout of a fluvial system is tested by the performance of some modeling essays in a hydraulic pilot channel.

scholarly journals GEOMETRIC FEATURES ANALYSIS FOR THE CLASSIFICATION OF CULTURAL HERITAGE POINT CLOUDS

2019 ◽  
Vol XLII-2/W15 ◽  
pp. 541-548 ◽  
Author(s):  
E. Grilli ◽  
E. M. Farella ◽  
A. Torresani ◽  
F. Remondino
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Cultural Heritage ◽  
Point Clouds ◽  
Geometric Features ◽  
3D Point Clouds ◽  
3D Data ◽  
3D Documentation ◽  
The Impact

<p><strong>Abstract.</strong> In the last years, the application of artificial intelligence (Machine Learning and Deep Learning methods) for the classification of 3D point clouds has become an important task in modern 3D documentation and modelling applications. The identification of proper geometric and radiometric features becomes fundamental to classify 2D/3D data correctly. While many studies have been conducted in the geospatial field, the cultural heritage sector is still partly unexplored. In this paper we analyse the efficacy of the geometric covariance features as a support for the classification of Cultural Heritage point clouds. To analyse the impact of the different features calculated on spherical neighbourhoods at various radius sizes, we present results obtained on four different heritage case studies using different features configurations.</p>

3D Reconstruction of Large Point Clouds with a New Point Correspondence Algorithm

2012 ◽  
Author(s):  
Rogério Yugo Takimoto ◽  
Renato Vogelaar ◽  
Edson Kenji Ueda ◽  
Marcos S.G. Tsuzuki ◽  
Toshiyuki Gotoh ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
Point Clouds ◽  
Point Correspondence

An Iterative Closest Point Algorithm Based on Biunique Correspondence of Point Clouds for 3D Reconstruction

2015 ◽  
Vol 35 (5) ◽  
pp. 0515003 ◽  
Author(s):  
韦盛斌 Wei Shengbin ◽  
王少卿 Wang Shaoqing ◽  
周常河 Zhou Changhe ◽  
刘昆 Liu Kun ◽  
范鑫 Fan Xin
Keyword(s):  
3D Reconstruction ◽  
Point Clouds ◽  
Iterative Closest Point ◽  
Iterative Closest Point Algorithm

Web Ontology Languages

2011 ◽  
pp. 96-109 ◽  
Author(s):  
G. Antoniou
Keyword(s):  
Semantic Web ◽  
General Introduction ◽  
Ontology Languages ◽  
Current Standards ◽  
The Web ◽  
Open Issues

Web ontology languages will be the main carriers of the information that we will want to share and integrate. The aim of this chapter is to give a general introduction to some of the ontology languages that play a prominent role on the Semantic Web. In particular, it will explain the role of ontologies on the Web and in ICT, review the current standards of RDFS and OWL, and discuss open issues for further developments.

scholarly journals Iterative K-Closest Point Algorithms for Colored Point Cloud Registration

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5331
Author(s):  
Ouk Choi ◽  
Min-Gyu Park ◽  
Youngbae Hwang
Keyword(s):  
Real World ◽  
Point Cloud ◽  
Point Clouds ◽  
The Other ◽  
Iterative Closest Point ◽  
Depth Images ◽  
The Cost ◽  
Soft Matching ◽  
Colored Point ◽  
Refinement Algorithm

We present two algorithms for aligning two colored point clouds. The two algorithms are designed to minimize a probabilistic cost based on the color-supported soft matching of points in a point cloud to their K-closest points in the other point cloud. The first algorithm, like prior iterative closest point algorithms, refines the pose parameters to minimize the cost. Assuming that the point clouds are obtained from RGB-depth images, our second algorithm regards the measured depth values as variables and minimizes the cost to obtain refined depth values. Experiments with our synthetic dataset show that our pose refinement algorithm gives better results compared to the existing algorithms. Our depth refinement algorithm is shown to achieve more accurate alignments from the outputs of the pose refinement step. Our algorithms are applied to a real-world dataset, providing accurate and visually improved results.

Sign in / Sign up

Export Citation Format

Share Document