scholarly journals Application of Territorial Laser Scanning in 3D Modeling of Traditional Village: A Case Study of Fenghuang Village in China

2021 ◽  
Vol 10 (11) ◽  
pp. 770
Author(s):  
Guiye Lin ◽  
Andrea Giordano ◽  
Kun Sang ◽  
Luigi Stendardo ◽  
Xiaochun Yang
Keyword(s):  
Laser Scanning ◽  
Cloud Model ◽  
Point Clouds ◽  
Historical Buildings ◽  
Complex Objects ◽  
Preservation Planning ◽  
Efficient Operation ◽  
Data Process ◽  
Architectural Patterns ◽  
Point Cloud Model

Historical villages bear historical, cultural, architectural, aesthetic, and landscape values, but they are facing a series of dangers and problems during the process of urbanization. Digital survey for traditional villages plays a crucial role in the preservation, planning, and development of this kind of heritage. The introduction of the terrestrial laser scanning technique is essential for heritage surveying, mapping, and modeling due to its advantages of noncontact measurement, accurate sensing of complex objects, and efficient operation. In recent years, TLS and related processing software (“SCENE”) have been widely presented as effective techniques for dealing with the management and protection of historical buildings in Fenghuang village. Thus, this paper highlights the process of using laser scanning to obtain architectural data, process point clouds, and compare the characteristics of historical buildings in Fenghuang village. The cloud-to-cloud registration technique is applied to build point clouds. As a result of model construction, some architectural patterns are summarized in this village, such as the spatial sequence of ancestral halls, the dominant position of memorial halls, and the character of building decorations and roof slopes. Furthermore, a BIM model is also explained to fulfill the statistical function for architectural components. In the future, more research can be fulfilled based on the built point cloud model, which will be beneficial for the development of the whole village.

scholarly journals MULTI-SENSOR 3D RECORDING PIPELINE FOR THE DOCUMENTATION OF JAVANESE TEMPLES

2019 ◽  
Vol XLII-2/W15 ◽  
pp. 829-834
Author(s):  
A. Murtiyos ◽  
P. Grussenmeyer ◽  
D. Suwardhi ◽  
W. A. Fadilah ◽  
H. A. Permana ◽  
...  
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Cloud Model ◽  
Point Clouds ◽  
Heritage Sites ◽  
Advantages And Disadvantages ◽  
3D Point Clouds ◽  
Point Cloud Model ◽  
Geometric Quality ◽  
Different Characteristics

<p><strong>Abstract.</strong> 3D recording is an important procedure in the conservation of heritage sites. This past decade, a myriad of 3D sensors has appeared in the market with different advantages and disadvantages. Most notably, the laser scanning and photogrammetry methods have become some of the most used techniques in 3D recording. The integration of these different sensors is an interesting topic, one which will be discussed in this paper. Integration is an activity to combine two or more data with different characteristics to produce a 3D model with the best results. The discussion in this study includes the process of acquisition, processing, and analysis of the geometric quality from the results of the 3D recording process; starting with the acquisition method, registration and georeferencing process, up to the integration of laser scanning and photogrammetry 3D point clouds. The final result of the integration of the two point clouds is the 3D point cloud model that has become a single entity. Some detailed parts of the object of interest draw both geometric and textural information from photogrammetry, while laser scanning provided a point cloud depicting the overall overview of the building. The object used as our case study is Sari Temple, located in Special Region of Yogyakarta, Indonesia.</p>

scholarly journals GEOREFERENCING AND REPROJECTION ERROR INVESTIGATION ON IMAGE BASED 3D DIGITIZATION AND MAPPING OF HISTORICAL BUILDINGS

2019 ◽  
Vol XLII-2/W11 ◽  
pp. 71-75
Author(s):  
C. Altuntas
Keyword(s):  
Point Cloud ◽  
Large Scale ◽  
Cloud Model ◽  
Low Cost ◽  
Three Dimensional ◽  
Control Points ◽  
Historical Buildings ◽  
Reprojection Error ◽  
Dense Point ◽  
Point Cloud Model

<p><strong>Abstract.</strong> Image based dense point cloud creation is easy and low-cost application for three dimensional digitization of small and large scale objects and surfaces. It is especially attractive method for cultural heritage documentation. Reprojection error on conjugate keypoints indicates accuracy of the model and keypoint localisation in this method. In addition, sequential registration of the images from large scale historical buildings creates big cumulative registration error. Thus, accuracy of the model should be increased with the control points or loop close imaging. The registration of point point cloud model into the georeference system is performed using control points. In this study historical Sultan Selim Mosque that was built in sixteen century by Great Architect Sinan was modelled via photogrammetric dense point cloud. The reprojection error and number of keypoints were evaluated for different base/length ratio. In addition, georeferencing accuracy was evaluated with many configuration of control points with loop and without loop closure imaging.</p>

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.

Three Dimensional Modeling of Buildings Using Three Dimensional Laser Scanning Data

2012 ◽  
Vol 594-597 ◽  
pp. 2398-2401
Author(s):  
Dong Ling Ma ◽  
Jian Cui ◽  
Fei Cai
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
3D Visualization ◽  
Cloud Model ◽  
Three Dimensional ◽  
3D Models ◽  
Three Dimensional Modeling ◽  
Dimensional Modeling ◽  
Feature Lines ◽  
Point Cloud Model

This paper provides a scheme to construct three dimensional (3D) model fast using laser scanning data. In the approach, firstly, laser point cloud are scanned from different scan positions and the point cloud coming from neighbor scan stations are spliced automatically to combine a uniform point cloud model, and then feature lines are extracted through the point cloud, and the framework of the building are extracted to generate 3D models. At last, a conclusion can be drawn that 3D visualization model can be generated quickly using 3D laser scanning technology. The experiment result shows that it will bring the application model and technical advantage which traditional mapping way can not have.

scholarly journals A COMPARATIVE STUDY AMONG THREE REGISTRATION ALGORITHMS: PERFORMANCE, QUALITY ASSURANCE AND ACCURACY

2019 ◽  
Vol XLII-2/W9 ◽  
pp. 779-786 ◽  
Author(s):  
D. Wujanz ◽  
L. Barazzetti ◽  
M. Previtali ◽  
M. Scaioni
Keyword(s):  
Laser Scanning ◽  
Point Clouds ◽  
Quality Measures ◽  
3D Models ◽  
Multiple Point ◽  
Historical Buildings ◽  
Common Reference ◽  
Performance Quality ◽  
Systematic Biases ◽  
Iterative Closest Point Algorithm

<p><strong>Abstract.</strong> A critical task in every terrestrial laser scanning project is the transformation (addressed to as registration or alignment) of multiple point clouds into a common reference system. Even though this operation appears to be a solved and well-understood problem, the vast majority of available techniques still lack meaningful quality measures that allow the user to understand and analyze the final outputs. The erroneous estimation of registration parameters may cause systematic biases that falsify those subsequently outcomes such as deformation measurements on historical buildings, CAD-drawings of individual elements, or 3D models devoted to analyze the verticality of a tower. Thus, this article compares three common registration algorithms, namely target-based registration, the Iterative-Closest Point algorithm (ICP) as well as a plane-based approach on examples related to different case studies concerning historical buildings.</p>

scholarly journals Research on the Involvement of Computer Graphics Algorithms in Systems for the Creation of Public Sculpture

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Acheng Zhou ◽  
Chao Gao
Keyword(s):  
Computer Graphics ◽  
Computer Image ◽  
Point Cloud ◽  
Laser Scanning ◽  
Cloud Model ◽  
High Definition ◽  
Cloud Data ◽  
Point Cloud Model ◽  
The Creation ◽  
Public Sculpture

Currently, there is less research on how to improve the efficiency of the application of computer graphics technology in the creation of public sculpture. Therefore, this paper will focus on how computer graphics algorithms can enable systems for the creation of public sculpture with the intervention of computer graphics technology to create more accurate and completed works of public sculpture. It will explore and analyze how computer image algorithms can help creators apply computer image technology to finish complete and accurate public sculptures, and individual studies, computer imagery, and model analysis are also used. In systems for the creation of public sculpture, the point cloud data of the model is obtained through 3D laser scanning technology; then the algorithm of the point cloud model is integrated and the Statistical Outlier Removal algorithm of the point cloud model intervention is processed. By this way, the point cloud model of the work is optimized, and then a more completed and accurate public sculpture work can be produced by 3D sculpting or 3D printing. The research shows that, in the creation of public sculptures with the intervention of computer graphics technology, the computer graphics algorithm acquires the basis of the high-definition public sculpture data model. The computer graphics algorithm improves the accuracy and completeness of the creator using computer graphics technology; it is also the key to transform the accurate enlargement and transformation of the sculptural model into the actual sculptural work.

scholarly journals AUTOMATIC INTEGRATION OF LASER SCANNING AND PHOTOGRAMMETRIC POINT CLOUDS: FROM ACQUISITION TO CO-REGISTRATION

2021 ◽  
Vol XLIII-B1-2021 ◽  
pp. 85-92
Author(s):  
T. Partovi ◽  
M. Dähne ◽  
M. Maboudi ◽  
D. Krueger ◽  
M. Gerke
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
High Capacity ◽  
Point Clouds ◽  
Complex Objects ◽  
Initial Image ◽  
Joint Project ◽  
3D Point Clouds ◽  
Image Capturing ◽  
Data Capturing

Abstract. Laser scanning systems have been developed to capture very high-resolution 3D point clouds and consequently acquire the object geometry. This object measuring technique has a high capacity for being utilized in a wide variety of applications such as indoor and outdoor modelling. The Terrestrial Laser Scanning (TLS) is used as an important data capturing measurement system to provide high quality point cloud from industrial or built-up environments. However, the static nature of the TLS and complexity of the industrial sites necessitate employing a complementary data capturing system e.g. cameras to fill the gaps in the TLS point cloud caused by occlusions which is very common in complex industrial areas. Moreover, employing images provide better radiometric and edge information. This motivated a joint project to develop a system for automatic and robust co-registration of TLS data and images directly, especially for complex objects. In this paper, the proposed methods for various components of this project including gap detection from point cloud, calculation of initial image capturing configuration, user interface and support system for the image capturing procedures, and co-registration between TLS point cloud and photogrammetric point cloud are presented. The primarily results on a complex industrial environment are promising.

Discrete Stress Analysis on Point-Cloud Model Derived From Medical Images

2009 ◽  
Author(s):  
Jia Lu ◽  
Jing Qian
Keyword(s):  
Finite Element ◽  
Point Cloud ◽  
Solid Mechanics ◽  
Medical Images ◽  
Cloud Model ◽  
Point Clouds ◽  
Mechanical Analysis ◽  
Patient Specific ◽  
Element Mesh ◽  
Point Cloud Model

Pixel or voxel data from the medical images provide a point-cloud depiction for complicated anatomies that are difficult to describe in CAD geometry. Traditionally, a point-cloud model needs to be converted into finite element mesh in order to perform mechanical analysis. Although meshing generation tools have been significantly improved over the last decades, generating high quality meshes in complicated bodies remains a challenge. Recently, the authors developed a family of solid mechanics solvers that work directly on domains represented by point-clouds [1,2]. Using this method, it is possible to conduct mechanical analysis on point-cloud representations of patient-specific organs without resorting to finite element method. In this article, we describe this paradigm of analysis and demonstrate the method with numerical examples.

scholarly journals Hole Repairing Algorithm for 3D Point Cloud Model of Symmetrical Objects Grasped by the Manipulator

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7558
Author(s):  
Linyan Cui ◽  
Guolong Zhang ◽  
Jinshen Wang
Keyword(s):  
Point Cloud ◽  
Cloud Model ◽  
Engineering Application ◽  
Point Clouds ◽  
Real Point ◽  
3D Point Cloud ◽  
Virtual Camera ◽  
3D Point Clouds ◽  
Cloud Models ◽  
Point Cloud Model

For the engineering application of manipulator grasping objects, mechanical arm occlusion and limited imaging angle produce various holes in the reconstructed 3D point clouds of objects. Acquiring a complete point cloud model of the grasped object plays a very important role in the subsequent task planning of the manipulator. This paper proposes a method with which to automatically detect and repair the holes in the 3D point cloud model of symmetrical objects grasped by the manipulator. With the established virtual camera coordinate system and boundary detection, repair and classification of holes, the closed boundaries for the nested holes were detected and classified into two kinds, which correspond to the mechanical claw holes caused by mechanical arm occlusion and the missing surface produced by limited imaging angle. These two kinds of holes were repaired based on surface reconstruction and object symmetry. Experiments on simulated and real point cloud models demonstrate that our approach outperforms the other state-of-the-art 3D point cloud hole repair algorithms.

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