Accuracy and precision of the three-dimensional assessment of the facial surface using a 3-D laser scanner

2006 ◽  
Vol 25 (6) ◽  
pp. 742-754 ◽  
Author(s):  
L. Kovacs ◽  
A. Zimmermann ◽  
G. Brockmann ◽  
H. Baurecht ◽  
K. Schwenzer-Zimmerer ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Laser Scanner ◽  
Accuracy And Precision ◽  
Dimensional Assessment

scholarly journals ASSESSING THE ACCURACY AND PRECISION OF IMPERFECT POINT CLOUDS FOR 3D INDOOR MAPPING AND MODELING

2018 ◽  
Vol IV-4/W6 ◽  
pp. 3-10
Author(s):  
J. Chen ◽  
O. E. Mora ◽  
K. C. Clarke
Keyword(s):  
Low Cost ◽  
Random Noise ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Point Clouds ◽  
Accuracy And Precision ◽  
Wide Range ◽  
Sharp Edges ◽  
The Cost ◽  
Indoor Spaces

<p><strong>Abstract.</strong> In recent years, growing public interest in three-dimensional technology has led to the emergence of affordable platforms that can capture 3D scenes for use in a wide range of consumer applications. These platforms are often widely available, inexpensive, and can potentially find dual use in taking measurements of indoor spaces for creating indoor maps. Their affordability, however, usually comes at the cost of reduced accuracy and precision, which becomes more apparent when these instruments are pushed to their limits to scan an entire room. The point cloud measurements they produce often exhibit systematic drift and random noise that can make performing comparisons with accurate data difficult, akin to trying to compare a fuzzy trapezoid to a perfect square with sharp edges. This paper outlines a process for assessing the accuracy and precision of these imperfect point clouds in the context of indoor mapping by integrating techniques such as the extended Gaussian image, iterative closest point registration, and histogram thresholding. A case study is provided at the end to demonstrate use of this process for evaluating the performance of the Scanse Sweep 3D, an ultra-low cost panoramic laser scanner.</p>

Handheld Laser Scanner Research

2019 ◽  
Vol 952 (10) ◽  
pp. 47-54
Author(s):  
A.V. Komissarov ◽  
A.V. Remizov ◽  
M.M. Shlyakhova ◽  
K.K. Yambaev
Keyword(s):  
Point Cloud ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Test Site ◽  
Optical Systems ◽  
Advantages And Disadvantages ◽  
Site Survey ◽  
Laser Scanners ◽  
Three Dimensional Models ◽  
The Stability

The authors consider hand-held laser scanners, as a new photogrammetric tool for obtaining three-dimensional models of objects. The principle of their work and the newest optical systems based on various sensors measuring the depth of space are described in detail. The method of simultaneous navigation and mapping (SLAM) used for combining single scans into point cloud is outlined. The formulated tasks and methods for performing studies of the DotProduct (USA) hand-held laser scanner DPI?8X based on a test site survey are presented. The accuracy requirements for determining the coordinates of polygon points are given. The essence of the performed experimental research of the DPI?8X scanner is described, including scanning of a test object at various scanner distances, shooting a test polygon from various scanner positions and building point cloud, repeatedly shooting the same area of the polygon to check the stability of the scanner. The data on the assessment of accuracy and analysis of research results are given. Fields of applying hand-held laser scanners, their advantages and disadvantages are identified.

scholarly journals The Effect of Perioral Scan and Artificial Skin Markers on the Accuracy of Virtual Dentofacial Integration: Stereophotogrammetry Versus Smartphone Three-Dimensional Face-Scanning

2020 ◽  
Vol 18 (1) ◽  
pp. 229
Author(s):  
Hang-Nga Mai ◽  
Du-Hyeong Lee
Keyword(s):  
Three Dimensional ◽  
Laser Scanner ◽  
Statistical Analyses ◽  
Integrated Models ◽  
Image Integration ◽  
Positional Accuracy ◽  
Significant Difference ◽  
Face Scanning ◽  
Scanning Systems ◽  
Dimensional Face

This study evaluated the effects of different matching methods on the accuracy of dentofacial integration in stereophotogrammetry and smartphone face-scanning systems. The integration was done (N = 30) with different matching areas (n = 10), including teeth image only (TO), perioral area without markers (PN) and with markers (PM). The positional accuracy of the integrated models was assessed by measuring the midline linear deviations and incisal line canting between the experimental groups and laser scanner-based reference standards. Kruskal–Wallis and Mann–Whitney U tests were used for statistical analyses (α = 0.05). The PM method exhibited the smallest linear deviations in both systems; while the highest deviations were found in the TO in stereophotogrammetry; and in PN in smartphone. For the incisal line canting; the canting degree was the lowest in the PM method; followed by that in the TO and the PN in both systems. Although stereophotogrammetry generally exhibited higher accuracy than the smartphone; the two systems demonstrated no significant difference when the perioral areas were used for matching. The use of perioral scans with markers enables accurate dentofacial image integration; however; cautions should be given on the accuracy of the perioral image obtained without the use of markers.

scholarly journals Three dimensional assessment of segmented Le Fort I osteotomy planning and follow-up: a validation study

2021 ◽  
pp. 103707
Author(s):  
Oliver da Costa Senior ◽  
Lukas Vaes ◽  
Delphine Mulier ◽  
Reinhilde Jacobs ◽  
Constantinus Politis ◽  
...  
Keyword(s):  
Validation Study ◽  
Three Dimensional ◽  
Le Fort I Osteotomy ◽  
Le Fort ◽  
Dimensional Assessment ◽  
Le Fort I

scholarly journals Two-dimensional and Three-dimensional Assessment of the Upper Airway

2017 ◽  
Vol 35 (1) ◽  
pp. 357-362 ◽  
Author(s):  
Isabella Vilaza ◽  
Pamela Araya-Díaz ◽  
Hernán M Palomino
Keyword(s):  
Three Dimensional ◽  
Upper Airway ◽  
Two Dimensional ◽  
Dimensional Assessment

scholarly journals Comparison of Depth Camera and Terrestrial Laser Scanner in Monitoring Structural Deflections

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 201
Author(s):  
Michael Bekele Maru ◽  
Donghwan Lee ◽  
Kassahun Demissie Tola ◽  
Seunghee Park
Keyword(s):  
Optical Sensors ◽  
Point Cloud ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Point Clouds ◽  
Depth Camera ◽  
Terrestrial Laser Scanner ◽  
Cloud Data ◽  
3D Point Clouds ◽  
3D Information

Modeling a structure in the virtual world using three-dimensional (3D) information enhances our understanding, while also aiding in the visualization, of how a structure reacts to any disturbance. Generally, 3D point clouds are used for determining structural behavioral changes. Light detection and ranging (LiDAR) is one of the crucial ways by which a 3D point cloud dataset can be generated. Additionally, 3D cameras are commonly used to develop a point cloud containing many points on the external surface of an object around it. The main objective of this study was to compare the performance of optical sensors, namely a depth camera (DC) and terrestrial laser scanner (TLS) in estimating structural deflection. We also utilized bilateral filtering techniques, which are commonly used in image processing, on the point cloud data for enhancing their accuracy and increasing the application prospects of these sensors in structure health monitoring. The results from these sensors were validated by comparing them with the outputs from a linear variable differential transformer sensor, which was mounted on the beam during an indoor experiment. The results showed that the datasets obtained from both the sensors were acceptable for nominal deflections of 3 mm and above because the error range was less than ±10%. However, the result obtained from the TLS were better than those obtained from the DC.

Three-Dimensional Assessment of MRI-Guided Percutaneous Cryotherapy of Liver Metastases

2004 ◽  
Vol 183 (3) ◽  
pp. 707-712 ◽  
Author(s):  
Stuart G. Silverman ◽  
Maryellen R. M. Sun ◽  
Kemal Tuncali ◽  
Paul R. Morrison ◽  
Eric vanSonnenberg ◽  
...  
Keyword(s):  
Liver Metastases ◽  
Three Dimensional ◽  
Mri Guided ◽  
Dimensional Assessment
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