Three-dimensional Data Capture and Processing

2006 ◽  
pp. 59-77
Author(s):  
W. Feng ◽  
Y. F. Zhang ◽  
Y. F. Wu ◽  
Y. S. Wong
Keyword(s):  
Three Dimensional ◽  
Data Capture

scholarly journals MicroCT analysis of connectivity in porous structures: optimizing data acquisition and analytical methods in the context of tissue engineering

2020 ◽  
Vol 17 (165) ◽  
pp. 20190833
Author(s):  
Malavika Nair ◽  
Jennifer H. Shepherd ◽  
Serena M. Best ◽  
Ruth E. Cameron
Keyword(s):  
Tissue Engineering ◽  
Analytical Methods ◽  
Large Scale ◽  
Structural Parameters ◽  
Three Dimensional ◽  
Data Capture ◽  
Pixel Size ◽  
Scale Invariant ◽  
Structural Anisotropy

Micro-computed X-ray tomography (MicroCT) is one of the most powerful techniques available for the three-dimensional characterization of complex multi-phase or porous microarchitectures. The imaging and analysis of porous networks are of particular interest in tissue engineering due to the ability to predict various large-scale cellular phenomena through the micro-scale characterization of the structure. However, optimizing the parameters for MicroCT data capture and analyses requires a careful balance of feature resolution and computational constraints while ensuring that a structurally representative section is imaged and analysed. In this work, artificial datasets were used to evaluate the validity of current analytical methods by considering the effect of noise and pixel size arising from the data capture, and intrinsic structural anisotropy and heterogeneity. A novel ‘segmented percolation method’ was developed to exclude the effect of anomalous, non-representative features within the datasets, allowing for scale-invariant structural parameters to be obtained consistently and without manual intervention for the first time. Finally, an in-depth assessment of the imaging and analytical procedures are presented by considering percolation events such as micro-particle filtration and cell sieving within the context of tissue engineering. Along with the novel guidelines established for general pixel size selection for MicroCT, we also report our determination of 3 μm as the definitive pixel size for use in analysing connectivity for tissue engineering applications.

scholarly journals A Self-Assembly Portable Mobile Mapping System for Archeological Reconstruction Based on VSLAM-Photogrammetric Algorithm

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3952 ◽  
Author(s):  
* ◽  
*
Keyword(s):  
Self Assembly ◽  
Average Distance ◽  
Low Cost ◽  
Three Dimensional ◽  
Point Clouds ◽  
3D Models ◽  
Data Capture ◽  
Information Modeling ◽  
3D Point Clouds ◽  
Mean Square Errors

Three Dimensional (3D) models are widely used in clinical applications, geosciences, cultural heritage preservation, and engineering; this, together with new emerging needs such as building information modeling (BIM) develop new data capture techniques and devices with a low cost and reduced learning curve that allow for non-specialized users to employ it. This paper presents a simple, self-assembly device for 3D point clouds data capture with an estimated base price under €2500; furthermore, a workflow for the calculations is described that includes a Visual SLAM-photogrammetric threaded algorithm that has been implemented in C++. Another purpose of this work is to validate the proposed system in BIM working environments. To achieve it, in outdoor tests, several 3D point clouds were obtained and the coordinates of 40 points were obtained by means of this device, with data capture distances ranging between 5 to 20 m. Subsequently, those were compared to the coordinates of the same targets measured by a total station. The Euclidean average distance errors and root mean square errors (RMSEs) ranging between 12–46 mm and 8–33 mm respectively, depending on the data capture distance (5–20 m). Furthermore, the proposed system was compared with a commonly used photogrammetric methodology based on Agisoft Metashape software. The results obtained demonstrate that the proposed system satisfies (in each case) the tolerances of ‘level 1’ (51 mm) and ‘level 2’ (13 mm) for point cloud acquisition in urban design and historic documentation, according to the BIM Guide for 3D Imaging (U.S. General Services).

scholarly journals Preserving the Impossible: Conservation of Soft-Sediment Hominin Footprint Sites and Strategies for Three-Dimensional Digital Data Capture

PLoS ONE ◽  
2013 ◽  
Vol 8 (4) ◽  
pp. e60755 ◽  
Author(s):  
Matthew R. Bennett ◽  
Peter Falkingham ◽  
Sarita A. Morse ◽  
Karl Bates ◽  
Robin H. Crompton
Keyword(s):  
Three Dimensional ◽  
Data Capture ◽  
Digital Data ◽  
Soft Sediment

scholarly journals VIRTUAL PALEONTOLOGY—AN OVERVIEW

2016 ◽  
Vol 22 ◽  
pp. 1-20 ◽  
Author(s):  
Mark Sutton ◽  
Imran Rahman ◽  
Russell Garwood
Keyword(s):  
Laser Scanning ◽  
Focused Ion Beam ◽  
Compositional Data ◽  
Ion Beam ◽  
Optical Tomography ◽  
Three Dimensional ◽  
Data Capture ◽  
Reconstruction Methods ◽  
Technological Developments ◽  
Capture Techniques

AbstractVirtual paleontology is the study of fossils through three-dimensional digital visualizations; it represents a powerful and well-established set of tools for the analysis and dissemination of fossil data. Techniques are divisible into tomographic (i.e., slice-based) and surface-based types. Tomography has a long predigital history, but the recent explosion of virtual paleontology has resulted primarily from developments in X-ray computed tomography (CT), and of surface-based technologies (e.g., laser scanning). Destructive tomographic methods include forms of physical-optical tomography (e.g., serial grinding); these are powerful but problematic techniques. Focused Ion Beam (FIB) tomography is a modern alternative for microfossils; it is also destructive but is capable of extremely high resolutions. Nondestructive tomographic methods include the many forms of CT, which are the most widely used data-capture techniques at present, but are not universally applicable. Where CT is inappropriate, other nondestructive technologies (e.g., neutron tomography, magnetic resonance imaging, optical tomography) can prove suitable. Surface-based methods provide portable and convenient data capture for surface topography and texture, and might be appropriate when internal morphology is not of interest; technologies include laser scanning, photogrammetry, and mechanical digitization. Reconstruction methods that produce visualizations from raw data are many and various; selection of an appropriate workflow will depend on many factors, but is an important consideration that should be addressed prior to any study. The vast majority of three-dimensional fossils can now be studied using some form of virtual paleontology, and barriers to broader adaptation are being eroded. Technical issues regarding data sharing remain problematic. Technological developments continue; those promising tomographic recovery of compositional data are of particular relevance to paleontology.

scholarly journals Influence of Scanner Precision and Analysis Software in Quantifying Three-Dimensional Intraoral Changes: Two-Factor Factorial Experimental Design

10.2196/17150 ◽  
2020 ◽  
Vol 22 (11) ◽  
pp. e17150
Author(s):  
Saoirse O'Toole ◽  
David Bartlett ◽  
Andrew Keeling ◽  
John McBride ◽  
Eduardo Bernabe ◽  
...  
Keyword(s):  
Primary Care ◽  
Volume Change ◽  
Three Dimensional ◽  
Data Capture ◽  
Maximum Point ◽  
Primary Care System ◽  
Factorial Experimental Design ◽  
Analysis Software ◽  
Average Profile ◽  
Profile Loss

Background Three-dimensional scans are increasingly used to quantify biological topographical changes and clinical health outcomes. Traditionally, the use of 3D scans has been limited to specialized centers owing to the high cost of the scanning equipment and the necessity for complex analysis software. Technological advances have made cheaper, more accessible methods of data capture and analysis available in the field of dentistry, potentially facilitating a primary care system to quantify disease progression. However, this system has yet to be compared with previous high-precision methods in university hospital settings. Objective The aim of this study was to compare a dental primary care method of data capture (intraoral scanner) with a precision hospital-based method (laser profilometer) in addition to comparing open source and commercial software available for data analysis. Methods Longitudinal dental wear data from 30 patients were analyzed using a two-factor factorial experimental design. Bimaxillary intraoral digital scans (TrueDefinition, 3M, UK) and conventional silicone impressions, poured in type-4 dental stone, were made at both baseline and follow-up appointments (mean 36 months, SD 10.9). Stone models were scanned using precision laser profilometry (Taicaan, Southampton, UK). Three-dimensional changes in both forms of digital scans of the first molars (n=76) were quantitatively analyzed using the engineering software Geomagic Control (3D Systems, Germany) and freeware WearCompare (Leeds Digital Dentistry, UK). Volume change (mm3) was the primary measurement outcome. The maximum point loss (μm) and the average profile loss (μm) were also recorded. Data were paired and skewed, and were therefore compared using Wilcoxon signed-rank tests with Bonferroni correction. Results The median (IQR) volume change for Geomagic using profilometry and using the intraoral scan was –0.37 mm3 (–3.75-2.30) and +0.51 mm3 (–2.17-4.26), respectively (P<.001). Using WearCompare, the median (IQR) volume change for profilometry and intraoral scanning was –1.21 mm3 (–3.48-0.56) and –0.39 mm3 (–3.96-2.76), respectively (P=.04). WearCompare detected significantly greater volume loss than Geomagic regardless of scanner type. No differences were observed between groups with respect to the maximum point loss or average profile loss. Conclusions As expected, the method of data capture, software used, and measurement metric all significantly influenced the measurement outcome. However, when appropriate analysis was used, the primary care system was able to quantify the degree of change and can be recommended depending on the accuracy needed to diagnose a condition. Lower-resolution scanners may underestimate complex changes when measuring at the micron level.

Modeling evacuation in institutional space: Linking three-dimensional data capture, simulation, analysis, and visualization workflows for risk assessment and communication

2017 ◽  
Vol 18 (1) ◽  
pp. 173-192 ◽  
Author(s):  
Ian M Lochhead ◽  
Nick Hedley
Keyword(s):  
Information Science ◽  
Visual Analysis ◽  
Simulation Analysis ◽  
Three Dimensional ◽  
Human Movement ◽  
Data Capture ◽  
Geographical Information ◽  
Exploratory Research ◽  
Game Engines ◽  
Institutional Space

This article presents exploratory research to develop new workflows that address the challenges of adequately capturing the geometry and topology of complex institutional spaces, the analysis of prescriptive evacuation plans, and the simulation of human movement and behavior in emergency scenarios. We present a collection of geovisual analytical environments that were developed to permit new ways to view and assess risk, evacuation, and human movement. Part of this research considers how different approaches to the representation of complex institutional space, using three-dimensional capture technologies at multiple resolutions (or derived from conventional formats, such as building plans), have implicit advantages or liabilities in the analysis of risk and human evacuation. We combine three-dimensional data capture methods with geographical information science theory, three-dimensional game engines, three-dimensional evacuation simulations and spatial analyses that address the variability of campus populations, and draw upon three-dimensional modeling and photogrammetry for the assessment of real-world features in digital space. The outcome of this research demonstrates agile workflows that address emergency planning requirements, but could also enable enhanced visual analysis and interactive learning by all campus citizens. Furthermore, this work reveals key considerations and limitations associated with the dynamic nature of evacuation events and the static environments in which they have been simulated.

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