scholarly journals Determining the relationship between the slope and directional distribution of the UAV point cloud and the accuracy of various IDW interpolation

2021 ◽  
Author(s):  
Kemal Özgür HASTAOĞLU ◽  
Sinan GÖĞSU ◽  
Yavuz GÜL
Keyword(s):  
Point Cloud ◽  
Directional Distribution ◽  
The Relationship

scholarly journals VALIDATION OF LIDAR SURVEY DATA BY COMPARISON OF SEVERAL UNCERTAINTY MODELS

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 1385-1390
Author(s):  
N. Seube
Keyword(s):  
Point Cloud ◽  
A Priori ◽  
A Posteriori ◽  
Data Set ◽  
Timing Errors ◽  
Beam Incidence ◽  
A Priori Uncertainty ◽  
Uncertainty Models ◽  
Attitude Uncertainty ◽  
The Relationship

Abstract. This paper introduce a new method for validating the precision of an airborne or a mobile LiDAR data set. The proposed method is based on the knowledge of an a Combined Standard Measurement Uncertainty (CSMU) model which describes LiDAR point covariance matrix and thus uncertainty ellipsoid. The model we consider includes timing errors and most importantly the incidence of the LiDAR beam. After describing the relationship between the beam incidence and other variable uncertainty (especially attitude uncertainty), we show that we can construct a CSMU model giving the covariance of each oint as a function of the relative geometry between the LiDAR beam and the point normal. The validation method we propose consist in comparing the CSMU model (predictive a priori uncertainty) t the Standard Deviation Alog the Surface Normal (SDASN), for all set of quasi planr segments of the point cloud. Whenever the a posteriori (i.e; observed by the SDASN) level of uncertainty is greater than a priori (i.e; expected) level of uncertainty, the point fails the validation test. We illustrate this approach on a dataset acquired by a Microdrones mdLiDAR1000 system.

scholarly journals Quantification Method for the Uncertainty of Matching Point Distribution on 3D Reconstruction

2020 ◽  
Vol 9 (4) ◽  
pp. 187
Author(s):  
Yuxia Bian ◽  
Xuejun Liu ◽  
Meizhen Wang ◽  
Hongji Liu ◽  
Shuhong Fang ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
Point Cloud ◽  
Point Distribution ◽  
Multiple Images ◽  
Quantification Method ◽  
Real Scene ◽  
Direct Data ◽  
The Relationship ◽  
Overlapping Region

Matching points are the direct data sources of the fundamental matrix, camera parameters, and point cloud calculation. Thus, their uncertainty has a direct influence on the quality of image-based 3D reconstruction and is dependent on the number, accuracy, and distribution of the matching points. This study mainly focuses on the uncertainty of matching point distribution. First, horizontal dilution of precision (HDOP) is used to quantify the feature point distribution in the overlapping region of multiple images. Then, the quantization method is constructed. H D O P ∗ ¯ , the average of 2 × arctan ( H D O P × n 5 − 1 ) / π on all images, is utilized to measure the uncertainty of matching point distribution on 3D reconstruction. Finally, simulated and real scene experiments were performed to describe and verify the rationality of the proposed method. We found that the relationship between H D O P ∗ ¯ and the matching point distribution in this study was consistent with that between matching point distribution and 3D reconstruction. Consequently, it may be a feasible method to predict the quality of 3D reconstruction by calculating the uncertainty of matching point distribution.

scholarly journals New indicators on fabric drape evaluation based on three-dimensional model

2019 ◽  
Vol 90 (11-12) ◽  
pp. 1291-1300
Author(s):  
Zhicai Yu ◽  
Yueqi Zhong ◽  
R. Hugh Gong ◽  
Haoyang Xie
Keyword(s):  
Point Cloud ◽  
Three Dimensional ◽  
Woven Fabrics ◽  
Woven Fabric ◽  
Angle Distribution ◽  
Bending Rigidity ◽  
Three Dimensional Model ◽  
Fabric Drape ◽  
Fabric Weight ◽  
The Relationship

To evaluate the ability of woven fabrics to drape in a more accurate way, a three-dimensional point cloud of a draped woven fabric was captured via an in-house drape-scanner. A new indicator, total drape angle (TDA), was proposed based on the three-dimensional fabric drape to characterize the ability of a woven fabric to drape. The relationship between TDA and the drape coefficient (DC) was analyzed to validate the performance of TDA. The result indicated that TDA is more stable and representative than the traditional DC in characterizing the ability of a woven fabric to drape. In addition, the drape angle distribution function (DADF) of the triangular mesh was employed to describe fabric drape, as well as to bridge the gap between drape configuration and the warp bending rigidity of woven fabric. The results showed that the correlation coefficient between the real warp bending rigidity value and what was predicted warp based on DADF and fabric weight was 0.952.

scholarly journals A NEW METHOD FOR DETERMINING THE DEFORMATION MONITORABLE INDICATOR OF POINT CLOUD

2016 ◽  
Vol III-7 ◽  
pp. 157-164
Author(s):  
W. Xuan ◽  
X. H. Hua ◽  
W. N. Qiu ◽  
J. G. Zou ◽  
X. J. Chen
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Sampling Interval ◽  
Deformation Monitoring ◽  
Error Space ◽  
Set Up ◽  
The Relationship ◽  
Error Ellipsoid ◽  
Actual Point

With the continuous development of the terrestrial laser scanning (TLS) technique, the precision of the laser scanning has been improved which makes it possible that TLS could be used for high-precision deformation monitoring. A deformation monitorable indicator (DMI) should be determined to distinguish the deformation from the error of point cloud and plays an important role in the deformation monitoring using TLS. After the DMI determined, a scheme of the deformation monitoring case could be planned to choose a suitable instrument, set up a suitable distance and sampling interval. In this paper, the point error space and the point cloud error space are modelled firstly based on the point error ellipsoid. Secondly, the actual point error is derived by the relationship between the actual point cloud error space and the point error space. Then, the DMI is determined using the actual point error. Finally, two sets of experiments is carried out and the feasibility of the DMI is proved.

scholarly journals SCAN-TO-BIM vs 3D IDEAL MODEL HBIM: PARAMETRIC TOOLS TO STUDY DOMES GEOMETRY

2019 ◽  
Vol XLII-2/W9 ◽  
pp. 219-226 ◽  
Author(s):  
M. Capone ◽  
E. Lanzara
Keyword(s):  
Point Cloud ◽  
Geometric Model ◽  
Data Interpretation ◽  
Research Field ◽  
Parametric Models ◽  
Building Information Modelling ◽  
Management Actions ◽  
Modeling Process ◽  
Building Information ◽  
The Relationship

<p><strong>Abstract.</strong> The contribution is part of an interdisciplinary research that aims to address the problems of knowledge, interpretation and documentation of vulnerable structures such as the brick Renaissance domes in Campania (XV-XVI century). The goal is to analyze the relationship between Survey, Historic Building Information Modelling (HBIM) and 3D parametric models based on geometric rules from Treaties to study and to manage Cultural Heritage. HBIM is generally based on scan-to-BIM process that allows to generate 3D model from point cloud. The reverse modeling process, from a point cloud to parametric geometric model, poses a series of issues at the center of cultural debate that currently takes place around HBIM. The experimentation underway is part of this research field with the aim of using the parametric approach as a tool able to introduce an additional methodology for big data interpretation. Currently we can identify two different approaches for the construction of a HBIM system: building a simplified model by identifying the shape grammar or building the geometric components from survey without using pre-compiled objects libraries, following the scan to BIM logic. In our research we are going to identify an "hybrid" methodology. Generally the process is based on the knowledge and critical abilities of individual scholars, the idea is to increase the efficiency of the system through collaborative workflow forms that allow to optimize the processes through effective knowledge management actions. We are going to use procedural modeling techniques to generate HBIM domes library.</p>

Three-Dimensional Structure Trajectory Guiding Scan and Points Cloud Registration

2013 ◽  
Vol 300-301 ◽  
pp. 423-426
Author(s):  
Yong Cai
Keyword(s):  
Point Cloud ◽  
Structural Parameters ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
Surface Model ◽  
Visual Measurement ◽  
Local Point ◽  
Inverse Kinematics Problem ◽  
The Relationship ◽  
Measurement Approach

Three-dimensional visual scanning is an advanced non-contact measurement approach that can obtain a complete surface model of object. But, in the method, the local raster point cloud sets calculated must be registered to a whole. To reduce fluctuating errors and increase efficiency, we propose a new method that scanner can be moved around object guided by pre-planning trajectory of the robot. First, considering the structural parameters of the robot, the Inverse Kinematics Problem of each joint rotating function is derived, and the moving trajectory is simulated. Then, the relationship between the distances of controlled motion and data gotten by scanner is analyzed, a transform matrix which registered the local point cloud sets is deduced, the raster data can be normalized to the world coordinate by it. The experimental results show that error of registration is less than 0.09mm. The method is suited to measuring different targets in robot workspace. It can improve the efficiency and flexibility of visual measurement system.

scholarly journals Leaf area index mapping with optical methods and allometric models in SMEAR flux tower footprint at Järvselja, Estonia

2015 ◽  
Vol 63 (1) ◽  
pp. 85-99
Author(s):  
Marta Mõistus ◽  
Mait Lang
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Point Cloud ◽  
Forest Growth ◽  
Height Distribution ◽  
Area Index ◽  
Flux Tower ◽  
Gap Fraction ◽  
Plant Area Index ◽  
The Relationship

AbstractLeaf area index (LAI) characterizes the amount of photosynthetically active tissue in plant canopies. LAI is one of the key factors determining ecosystem net primary production and gas and energy exchange between the canopy and the atmosphere. The aim of the present study was to test different methods for LAI and effective plant area index (PAIe) estimation in mixed hemiboreal forests in Järvselja SMEAR Estonia (Station for Measuring Ecosystem-Atmosphere Relations) flux tower footprint. We used digital hemispherical images from sample plots, forest management inventory data, allometric foliage mass models, airborne discrete-return recording laser scanner (ALS) data and multispectral satellite images. The free ware program HemiSpherical Project Manager (HSP) was used to calculate canopy gap fraction from digital hemispherical photographs taken in 25 sample plots. PAIewas calculated from the gap fraction for up-scaling based on ALS point cloud metrics. The all ALS pulse returns-based canopy transmission was found to be the most suitable lidar metric to estimate PAIein Järvselja forests. The 95-percentile (H95) of lidar point cloud height distribution correlates very well with allometric regression models based LAI and in birch stands the relationship was fitted with 0.7 m2m−2residual error. However, the relationship was specific to each allometric foliage mass model and systematic discrepancies were detected at large LAI values between the models. Relationships between the spectral reflectance and allometric LAI were not good enough to be used for LAI mapping. Therefore, airborne laser scanning data-based PAIemap was created for areas near SMEAR tower. We recommend to establish a network of permanent sample plots for forest growth and gap fraction measurements into the flux footprint of SMEAR Estonia flux tower in Järvselja to provide consistent up to date data for interpretation of the flux measurements.

Simulation Design of Bionic Blade on Wind Turbine

2012 ◽  
Vol 479-481 ◽  
pp. 2215-2221
Author(s):  
Hai Feng Zhou ◽  
Chen He Du ◽  
Yuan Qing Huang
Keyword(s):  
Point Cloud ◽  
Element Model ◽  
Plant Leaves ◽  
Simulation Design ◽  
Natural Evolution ◽  
Blade Vibration ◽  
Bionic Blade ◽  
Numerical Simulation Methods ◽  
Vibration Modal ◽  
The Relationship

After millions of years of competition and the natural evolution of species, the biological nature (plant leaves) has formed a number of natural and rational structure. This form of the structure and organisms inherit environmental stress exist some connection. This paper as a study of plant leaves, using numerical simulation methods to explore the structure and mechanical properties of plant leaves the relationship between: Collection of fresh plant leaves, leaf through the AutoCAD software to obtain the coordinates of the point cloud, created in the ANSYS finite element model of a simplified blade, applied uniformly distributed wind load calculations to solve; and optimal blade vibration modal analysis program.

scholarly journals FORGOTTEN ARCHITECTURE: SMART TOOLS FOR CULTURAL TOURISM IN THE CLOISTER OF THE PRIOR (SANTA MARIA DELLE GRAZIE, MILAN)

2019 ◽  
Vol XLII-2/W11 ◽  
pp. 247-253 ◽  
Author(s):  
C. Bolognesi ◽  
D. Aiello
Keyword(s):  
Nineteenth Century ◽  
Point Cloud ◽  
Cultural Tourism ◽  
3D Modelling ◽  
Starting Point ◽  
Digital Contents ◽  
Good Point ◽  
History Of ◽  
The Relationship ◽  
Santa Maria

<p><strong>Abstract.</strong> This paper describes the relationship among an important nineteenth-century monument, the Cloister of the Prior (located in the convent of Santa Maria delle Grazie, Milan), its survey and the technical integration of different cultural information to be enjoyed in VR and AR during its visit. In this context, the surveying techniques have to face the problem related to the presence of white and smooth surfaces and the difficulty in obtaining a good result in the 3D modelling. Various tests have been performed to create a good point cloud from the photogrammetric survey of the cloister, conducted through the use of different camera lenses or post production interventions applied to the images, in order to obtain the best results. The 3D modelling is not only a base for creating virtual and augmented experiences (that, through digital contents, explain to the distracted public the history of this less known part of the monument) but also a starting point for possible further studies focused on the modifications that affected the cloister over the centuries.</p>

scholarly journals Filling the binary images of draped fabric with pix2pix convolutional neural network

2020 ◽  
Vol 15 ◽  
pp. 155892502092154
Author(s):  
Zhicai Yu ◽  
Yueqi Zhong ◽  
R Hugh Gong ◽  
Haoyang Xie
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Point Cloud ◽  
Three Dimensional ◽  
Ground Truth ◽  
Binary Image ◽  
Grayscale Image ◽  
Binary Images ◽  
The Relationship ◽  
Grayscale Images

To fill the binary image of draped fabric into a comparable grayscale image with detailed shade information, the three-dimensional point cloud of draped fabric was obtained with a self-built three-dimensional scanning device. The three-dimensional point cloud of drape fabric is encapsulated into a triangular mesh, and the binary and grayscale images of draped fabric were rendered in virtual environments separately. A pix2pix convolutional neural network with the binary image of draped fabric as input and the grayscale image of draped fabric as output was constructed and trained. The relationship between the binary image and the grayscale image was established. The results show that the trained pix2pix neural network can fill unknown binary top view images of draped fabric to grayscale images. The average pixel cosine similarity between filling results and ground truth could reach 0.97.

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