scholarly journals USING AFFORDABLE DATA CAPTURING DEVICES FOR AUTOMATIC 3D CITY MODELLING

2017 ◽  
Vol XLII-4/W6 ◽  
pp. 9-13 ◽  
Author(s):  
B. Alizadehashrafi ◽  
A. Abdul-Rahman
Keyword(s):  
Image Matching ◽  
3D Model ◽  
Point Clouds ◽  
3D Models ◽  
Parallel Projection ◽  
Passive Remote Sensing ◽  
Data Capturing ◽  
3D City Modelling ◽  
Very High ◽  
Ar Drone

In this research project, many movies from UTM Kolej 9, Skudai, Johor Bahru (See Figure 1) were taken by AR. Drone 2. Since the AR drone 2.0 has liquid lens, while flying there were significant distortions and deformations on the converted pictures of the movies. Passive remote sensing (RS) applications based on image matching and Epipolar lines such as Agisoft PhotoScan have been tested to create the point clouds and mesh along with 3D models and textures. As the result was not acceptable (See Figure 2), the previous Dynamic Pulse Function based on Ruby programming language were enhanced and utilized to create the 3D models automatically in LoD3. The accuracy of the final 3D model is almost 10 to 20 cm. After rectification and parallel projection of the photos based on some tie points and targets, all the parameters were measured and utilized as an input to the system to create the 3D model automatically in LoD3 in a very high accuracy.

scholarly journals A PROJECTION-BASED RECONSTRUCTION ALGORITHM FOR 3D MODELING OF BRIDGE STRUCTURES FROM DRONE-BASED POINT CLOUD

2021 ◽  
Vol XLVI-4/W1-2021 ◽  
pp. 77-83
Author(s):  
M. Mehranfar ◽  
H. Arefi ◽  
F. Alidoost
Keyword(s):  
Point Cloud ◽  
Clustering Algorithm ◽  
3D Model ◽  
Reconstruction Algorithm ◽  
Point Clouds ◽  
3D Models ◽  
Reconstruction Technique ◽  
Reconstruction Process ◽  
Median Error ◽  
Bridge Structures

Abstract. This paper presents a projection-based method for 3D bridge modeling using dense point clouds generated from drone-based images. The proposed workflow consists of hierarchical steps including point cloud segmentation, modeling of individual elements, and merging of individual models to generate the final 3D model. First, a fuzzy clustering algorithm including the height values and geometrical-spectral features is employed to segment the input point cloud into the main bridge elements. In the next step, a 2D projection-based reconstruction technique is developed to generate a 2D model for each element. Next, the 3D models are reconstructed by extruding the 2D models orthogonally to the projection plane. Finally, the reconstruction process is completed by merging individual 3D models and forming an integrated 3D model of the bridge structure in a CAD format. The results demonstrate the effectiveness of the proposed method to generate 3D models automatically with a median error of about 0.025 m between the elements’ dimensions in the reference and reconstructed models for two different bridge datasets.

scholarly journals RGB-D Indoor Plane-based 3D-Modeling using Autonomous Robot

2014 ◽  
Vol XL-1 ◽  
pp. 301-308 ◽  
Author(s):  
N. Mostofi ◽  
A. Moussa ◽  
M. Elhabiby ◽  
N. El-Sheimy
Keyword(s):  
3D Modeling ◽  
3D Model ◽  
Research Work ◽  
Region Growing ◽  
Point Clouds ◽  
Visual Odometry ◽  
3D Models ◽  
Indoor Environments ◽  
Relative Pose ◽  
Matching Techniques

3D model of indoor environments provide rich information that can facilitate the disambiguation of different places and increases the familiarization process to any indoor environment for the remote users. In this research work, we describe a system for visual odometry and 3D modeling using information from RGB-D sensor (Camera). The visual odometry method estimates the relative pose of the consecutive RGB-D frames through feature extraction and matching techniques. The pose estimated by visual odometry algorithm is then refined with iterative closest point (ICP) method. The switching technique between ICP and visual odometry in case of no visible features suppresses inconsistency in the final developed map. Finally, we add the loop closure to remove the deviation between first and last frames. In order to have a semantic meaning out of 3D models, the planar patches are segmented from RGB-D point clouds data using region growing technique followed by convex hull method to assign boundaries to the extracted patches. In order to build a final semantic 3D model, the segmented patches are merged using relative pose information obtained from the first step.

scholarly journals Workflow for 3D geovisualization of the data obtained with the use of Unmanned Aerial Vehicle in Augmented Reality

2019 ◽  
Vol 1 ◽  
pp. 1-1
Author(s):  
Łukasz Halik ◽  
Maciej Smaczyński ◽  
Beata Medyńska-Gulij
Keyword(s):  
Augmented Reality ◽  
Large Scale ◽  
3D Model ◽  
Digital Terrain Model ◽  
Point Clouds ◽  
3D Models ◽  
Irregular Shape ◽  
Terrain Model ◽  
Natural Aggregate ◽  
Digital Terrain

<p><strong>Abstract.</strong> The attempt to work out the geomatic workflow of transforming low-level aerial imagery obtained with unmanned aerial vehicles (UAV) into a digital terrain model (DTM) and implementing the 3D model into the augmented reality (AR) system constitutes the main problem discussed in this article. The authors suggest the following workflow demonstrated in Fig. 1.</p><p>The series of pictures obtained by means of UAV equipped with a HD camera was the source of data to be worked out in the final stage of the geovisualization. The series was then processed and a few point clouds were isolated from it, being later used for generating test 3D models.</p><p>The practical aim of the research conducted was to work out, on the basis of the UAV pictures, the 3D geovisualization in the AR system that would depict the heap of the natural aggregate of irregular shape. The subsequent aim was to verify the accuracy of the produced 3D model. The object of the study was a natural aggregate heap of irregular shape and denivelations up to 11 meters.</p><p>Based on the obtained photos, three point clouds (varying in the level of detail) were generated for the 20&amp;thinsp;000-meter-square area. The several-centimeter differences observed between the control points in the field and the ones from the model might corroborate the usefulness of the described algorithm for creating large-scale DTMs for engineering purposes. The method of transformation of pictures into the point cloud that was subsequently transformed into 3D models was employed in the research, resulting in the scheme depicting the technological sequence of the creation of 3D geovisualization worked out in the AR system. The geovisualization can be viewed thanks to a specially worked out mobile application for smartphones.</p>

scholarly journals Surface reconstruction post-processing method for 3D- scanned objects

2021 ◽  
Vol 2086 (1) ◽  
pp. 012077
Author(s):  
P D Badillo ◽  
V A Parfenov ◽  
N L Shchegoleva
Keyword(s):  
3D Model ◽  
Real Life ◽  
Point Clouds ◽  
3D Models ◽  
Processing Method ◽  
Automatic Method ◽  
Post Processing ◽  
Scanning Procedure ◽  
Trained Personnel ◽  
Non Destructive

Abstract 3D scanning is widely used in multiple applications to obtain high precision / non-destructive documentation of real-life objects, which is especially important in Cultural Heritage (CH) preservation. However, some issues (in particular missing parts which are commonly known as “holes”) affect the accuracy of the obtained 3D model after the scanning procedure and requires time-consuming post-processing procedures, which include manual editing by highly-trained personnel. In this article an automatic method to reconstruct the obtained surface of 3D models is proposed, improving previously obtained results for high-density point clouds.

scholarly journals 3D DIGITIZATION OF AN HERITAGE MASTERPIECE - A CRITICAL ANALYSIS ON QUALITY ASSESSMENT

2016 ◽  
Vol XLI-B5 ◽  
pp. 675-683 ◽  
Author(s):  
F. Menna ◽  
E. Nocerino ◽  
F. Remondino ◽  
M. Dellepiane ◽  
M. Callieri ◽  
...  
Keyword(s):  
Critical Analysis ◽  
Laser Scanning ◽  
3D Model ◽  
3D Models ◽  
Range Imaging ◽  
Physical Size ◽  
Close Range ◽  
Short Time ◽  
3D Digitization ◽  
Very High

Despite being perceived as interchangeable when properly applied, close-range photogrammetry and range imaging have both their pros and limitations that can be overcome using suitable procedures. Even if the two techniques have been frequently cross-compared, critical analysis discussing all sub-phases of a complex digitization project are quite rare. Comparisons taking into account the digitization of a cultural masterpiece, such as the Etruscan Sarcophagus of the Spouses (Figure 1) discussed in this paper, are even less common. The final 3D model of the Sarcophagus shows impressive spatial and texture resolution, in the order of tenths of millimetre for both digitization techniques, making it a large 3D digital model even though the physical size of the artwork is quite limited. The paper presents the survey of the Sarcophagus, a late 6th century BC Etruscan anthropoid Sarcophagus. Photogrammetry and laser scanning were used for its 3D digitization in two different times only few days apart from each other. The very short time available for the digitization was a crucial constraint for the surveying operations (due to constraints imposed us by the museum curators). Despite very high-resolution and detailed 3D models have been produced, a metric comparison between the two models shows intrinsic limitations of each technique that should be overcome through suitable onsite metric verification procedures as well as a proper processing workflow.

scholarly journals 3D DIGITIZATION OF AN HERITAGE MASTERPIECE - A CRITICAL ANALYSIS ON QUALITY ASSESSMENT

2016 ◽  
Vol XLI-B5 ◽  
pp. 675-683 ◽  
Author(s):  
F. Menna ◽  
E. Nocerino ◽  
F. Remondino ◽  
M. Dellepiane ◽  
M. Callieri ◽  
...  
Keyword(s):  
Critical Analysis ◽  
Laser Scanning ◽  
3D Model ◽  
3D Models ◽  
Range Imaging ◽  
Physical Size ◽  
Close Range ◽  
Short Time ◽  
3D Digitization ◽  
Very High

Despite being perceived as interchangeable when properly applied, close-range photogrammetry and range imaging have both their pros and limitations that can be overcome using suitable procedures. Even if the two techniques have been frequently cross-compared, critical analysis discussing all sub-phases of a complex digitization project are quite rare. Comparisons taking into account the digitization of a cultural masterpiece, such as the Etruscan Sarcophagus of the Spouses (Figure 1) discussed in this paper, are even less common. The final 3D model of the Sarcophagus shows impressive spatial and texture resolution, in the order of tenths of millimetre for both digitization techniques, making it a large 3D digital model even though the physical size of the artwork is quite limited. The paper presents the survey of the Sarcophagus, a late 6th century BC Etruscan anthropoid Sarcophagus. Photogrammetry and laser scanning were used for its 3D digitization in two different times only few days apart from each other. The very short time available for the digitization was a crucial constraint for the surveying operations (due to constraints imposed us by the museum curators). Despite very high-resolution and detailed 3D models have been produced, a metric comparison between the two models shows intrinsic limitations of each technique that should be overcome through suitable onsite metric verification procedures as well as a proper processing workflow.

Representing 3D Model of Building From TLS Data Scanning in CityGML

2014 ◽  
Vol 71 (4) ◽  
Author(s):  
R. Akmaliaa ◽  
H. Setan ◽  
Z. Majid ◽  
D. Suwardhi
Keyword(s):  
3D Model ◽  
Semantic Information ◽  
Laser Scanner ◽  
Point Clouds ◽  
3D Models ◽  
Data Sources ◽  
Detailed Model ◽  
Building Model ◽  
Building Models ◽  
3D Building Model

Nowadays, 3D city models are used by the increasing number of applications. Most applications require not only geometric information but also semantic information. As a standard and tool for 3D city model, CityGML, provides a method for storing and managing both geometric and semantic information. Moreover, it also provides the multi-scale representation of 3D building model for efficient visualization. In CityGML, building models are represented in five LODs (Level of Detail), start from LOD0, LOD1, LOD2, LOD3, and LOD4. Each level has different accuracy and detail requirement for visualization. Usually, for obtaining multi-LOD of 3D building model, several data sources are integrated. For example, LiDAR data is used for generating LOD0, LOD1, and LOD2 as close-range photogrammetry data is used for generating more detailed model in LOD3 and LOD4. However, using additional data sources is increasing cost and time consuming. Since the development of TLS (Terrestrial Laser Scanner), data collection for detailed model can be conducted in a relative short time compared to photogrammetry. Point cloud generated from TLS can be used for generating the multi-LOD of building model. This paper gives an overview about the representation of 3D building model in CityGML and also method for generating multi-LOD of building from TLS data. An experiment was conducted using TLS. Following the standard in CityGML, point clouds from TLS were processed resulting 3D model of building in different level of details. Afterward, models in different LOD were converted into XML schema to be used in CityGML. From the experiment, final result shows that TLS can be used for generating 3D models of building in LOD1, LOD2, and LOD3.

From UAV-photogrammetry to displacement rates – monitoring slope deformations in Alpine terrain

2020 ◽  
Author(s):  
Christian Demmler ◽  
Marc Adams ◽  
Anne Hormes
Keyword(s):  
Change Detection ◽  
Active Sites ◽  
Laser Scanning ◽  
3D Model ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
3D Models ◽  
Total Station ◽  
In Situ Data ◽  
Expert Input

&lt;p&gt;Mountainous areas bring unique challenges for surveying and natural hazard monitoring &amp;#8211; inaccessibility, dangerous terrain, snow coverage and line-of-sight problems often make it next to impossible to perform ground-based monitoring or even to provide a good vantage point for close-range sensing (e.g. terrestrial laser scanning (TLS) or terrestrial photogrammetry). Airborne or satellite-based methods are often the only way to gain information about geodynamically active sites. Here, structure-from-motion (SfM) photogrammetry from unmanned aerial vehicle (UAV) imagery in particular can provide an inexpensive and easily implemented monitoring option. The Vigilans research project attempts to evaluate the feasibility of UAV-photogrammetry against more established surveying methods (e.g. in situ data from extensometers or total stations).&lt;/p&gt;&lt;p&gt;Our study site Marzellkamm is located in the Central &amp;#214;tztal Alps of Western Austria. The active rock slope deformation we are monitoring in Vigilans lies at 2450-2850&amp;#160;m asl. on a SE-facing slope. Annual displacement rates of up to 1.5 m/year in the early 2010&amp;#8217;s triggered monitoring and research interest. Due to the remote location, mitigation methods were not implemented, but a hiking trails was relocated. Orthoimage photogrammetry and ground-based monitoring instrumentation (extensometers, terrestrial laser scanning, total station measurements combined with GNSS and geodetic surveys) collected data 1971-2019.&lt;/p&gt;&lt;p&gt;In the last years, movement along the slope has slowed down considerably. The rather slow current movements provide a valuable challenge for detection, with rates of &lt;0.05&amp;#160;m/year occurring in the more stable upper sections, while the NW section in particular still shows pronounced movement of up to 0.3&amp;#160;m/year. For this reason, Marzellkamm provides excellent evaluation for new methods such as UAV-SfM.&lt;/p&gt;&lt;p&gt;In three separate missions between summer 2018 to fall of 2019, UAV-SfM 3D-models of the site were created for displacement rate evaluations; it is planned to continue this monitoring for a total of three years as part of the Vigilans project. Photogrammetric missions were performed in conjunction with total station measurements of more than 30 ground control points.&lt;/p&gt;&lt;p&gt;The required level of precision is becoming achievable and affordable with new RTK/PPK-equipped (Real-Time-Kinematics/Post-Processed Kinematics) UAVs. However, evaluating the resulting 3D-- model in terms of movement rates remains non-trivial. The most common algorithm for change detection in point clouds, M3C2, is not well-suited to detect a laterally moving surface as a whole, as it detects changes along the normal orientation of a surface (such as subsidence). Therefore, the point cloud needs to be very selectively reduced, requiring complex filtering operations and expert input as well as expensive software packages.&lt;/p&gt;&lt;p&gt;This contribution will present a workflow to simplify such evaluation, based on 2.5D (DEM-based) algorithms such as IMCORR and DoD (Difference-of-DEMs), in comparison with the more complex 3D-pointcloud based processing. The presented workflow is based on Agisoft Metashape and Open-Source software tools QGIS and Saga GIS. It aims to streamline UAV-based surveying work, 3D-model generation and simplified change detection into a repeatable and easily automatable framework. Special emphasis will be put on estimating the quality of the recorded data.&lt;/p&gt;

scholarly journals VIRTUAL RECONSTRUCTION OF LOST ARCHITECTURES: FROM THE TLS SURVEY TO AR VISUALIZATION

2016 ◽  
Vol XLI-B5 ◽  
pp. 383-390 ◽  
Author(s):  
R. Quattrini ◽  
R. Pierdicca ◽  
E. Frontoni ◽  
R. Barcaglioni
Keyword(s):  
3D Model ◽  
Low Cost ◽  
Point Clouds ◽  
3D Models ◽  
Virtual Model ◽  
Historical Sources ◽  
High Quality ◽  
Archaeological Heritage ◽  
Virtual Reconstruction ◽  
Historical Architecture

The exploitation of high quality 3D models for dissemination of archaeological heritage is currently an investigated topic, although Mobile Augmented Reality platforms for historical architecture are not available, allowing to develop low-cost pipelines for effective contents. The paper presents a virtual anastylosis, starting from historical sources and from 3D model based on TLS survey. Several efforts and outputs in augmented or immersive environments, exploiting this reconstruction, are discussed. &lt;br&gt;&lt;br&gt; The work demonstrates the feasibility of a 3D reconstruction approach for complex architectural shapes starting from point clouds and its AR/VR exploitation, allowing the superimposition with archaeological evidences. Major contributions consist in the presentation and the discussion of a pipeline starting from the virtual model, to its simplification showing several outcomes, comparing also the supported data qualities and advantages/disadvantages due to MAR and VR limitations.

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