scholarly journals Automatic Calibration of a Two-Axis Rotary Table for 3D Scanning Purposes

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7107
Author(s):  
Livio Bisogni ◽  
Ramtin Mollaiyan ◽  
Matteo Pettinari ◽  
Paolo Neri ◽  
Marco Gabiccini
Keyword(s):  
Point Clouds ◽  
3D Scanning ◽  
Optimal Number ◽  
Acquisition Time ◽  
Complex Geometries ◽  
Automatic Calibration ◽  
Camera System ◽  
Reprojection Error ◽  
Speed Up ◽  
Manual Registration

Rotary tables are often used to speed up the acquisition time during the 3D scanning of complex geometries. In order to avoid manual registration of the point clouds acquired with different orientations, automatic algorithms to compensate the rotation were developed. Alternatively, a proper calibration of the rotary axis with respect to the camera system is needed. Several methods are available in the literature, but they only consider a single-axis calibration. In this paper, a method for the simultaneous calibration of both axes of the table is proposed. A checkerboard is attached to the table, and several images with different poses are acquired. An optimization algorithm is then setup to determine the orientation and the locations of the two axes. A metric to assess the calibration quality was also defined by computing the average mean reprojection error. This metric is used to investigate the optimal number and distribution of the calibration poses, demonstrating that the optimum calibration results are achieved when a wider dispersion of the calibration poses is adopted.

scholarly journals Modeling and Processing of Smart Point Clouds of Cultural Relics with Complex Geometries

2021 ◽  
Vol 10 (9) ◽  
pp. 617
Author(s):  
Su Yang ◽  
Miaole Hou ◽  
Ahmed Shaker ◽  
Songnian Li
Keyword(s):  
Point Cloud ◽  
Semantic Information ◽  
Point Clouds ◽  
Information Modeling ◽  
Complex Geometries ◽  
3D Point Cloud ◽  
Point Cloud Data ◽  
Modeling Framework ◽  
Cloud Data ◽  
Cultural Relics

The digital documentation of cultural relics plays an important role in archiving, protection, and management. In the field of cultural heritage, three-dimensional (3D) point cloud data is effective at expressing complex geometric structures and geometric details on the surface of cultural relics, but lacks semantic information. To elaborate the geometric information of cultural relics and add meaningful semantic information, we propose a modeling and processing method of smart point clouds of cultural relics with complex geometries. An information modeling framework for complex geometric cultural relics was designed based on the concept of smart point clouds, in which 3D point cloud data are organized through the time dimension and different spatial scales indicating different geometric details. The proposed model allows smart point clouds or a subset to be linked with semantic information or related documents. As such, this novel information modeling framework can be used to describe rich semantic information and high-level details of geometry. The proposed information model not only expresses the complex geometric structure of the cultural relics and the geometric details on the surface, but also has rich semantic information, and can even be associated with documents. A case study of the Dazu Thousand-Hand Bodhisattva Statue, which is characterized by a variety of complex geometries, reveals that our proposed framework is capable of modeling and processing the statue with excellent applicability and expansibility. This work provides insights into the sustainable development of cultural heritage protection globally.

Choosing the optimal number of B-spline control points (Part 2: Approximation of surfaces and applications)

2017 ◽  
Vol 11 (1) ◽  
Author(s):  
Corinna Harmening ◽  
Hans Neuner
Keyword(s):  
Data Analysis ◽  
Laser Scanner ◽  
Point Clouds ◽  
Optimal Number ◽  
Deformation Analysis ◽  
Control Points ◽  
Trial And Error ◽  
B Spline ◽  
B Splines ◽  
Spline Surfaces

AbstractFreeform surfaces like B-splines have proven to be a suitable tool to model laser scanner point clouds and to form the basis for an areal data analysis, for example an areal deformation analysis.A variety of parameters determine the B-spline's appearance, the B-spline's complexity being mostly determined by the number of control points. Usually, this parameter type is chosen by intuitive trial-and-error-procedures.In [The present paper continues these investigations. If necessary, the methods proposed in [The application of those methods to B-spline surfaces reveals the datum problem of those surfaces, meaning that location and number of control points of two B-splines surfaces are only comparable if they are based on the same parameterization. First investigations to solve this problem are presented.

Converting Point Cloud to Revolved Solids

2013 ◽  
Vol 371 ◽  
pp. 468-472
Author(s):  
Mircea Viorel Drăgoi ◽  
Slobodan Navalušić
Keyword(s):  
Reverse Engineering ◽  
Cross Section ◽  
Software Package ◽  
Point Cloud ◽  
3D Model ◽  
Point Clouds ◽  
3D Scanning ◽  
Main Drawback ◽  
Mass Properties

3D scanning is one of the basic methods to gather data for reverse engineering. The main drawback of 3D scanning is that its output - the point cloud - can never be used directly to define surfaces or solids useful to reconstruct the electronic 3D model of the scanned part.The paper presents a piece of software designed in VisualLISP for AutoCAD, software that acts as a point cloud to 3D primitives converter. The novelty consists of the method used to find the parameters of the primitive that best fits to the point cloud: the mass properties of regions are used to find the center of a cones cross section. Parts have been scanned and the point clouds processed. The results obtained prove the correctness of the algorithm and of the method applied. A piece of software that processes the point cloud in order to find the 3D primitive that it fits the best has been developed. The output is the 3D primitive that successfully and accurate replaces the point cloud. Some adjacent tools were designed, so the entire software package becomes a useful tool for the reverse engineering user. The ways the researches can be continued and developed are foreseen, as well

scholarly journals A framework for non-ICP lidar-based pose estimation using an optimally constrained 3D target

2021 ◽  
Author(s):  
Pierre Saint-Cyr
Keyword(s):  
Pose Estimation ◽  
Full Range ◽  
Point Clouds ◽  
Initial Guess ◽  
Measurement Noise ◽  
Lidar Data ◽  
Lidar Measurement ◽  
Camera System ◽  
Icp Algorithm ◽  
Scan Data

This thesis describes a non-ICP-based framework fohr [sic] the computation of a pose estimate of a special target shape from raw LIDAR scan data. In previous work, an ideal unambiguously-shaped 3D target (the Reduced Ambiguity Cuboctahedron, or RAC) was designed for use in LIDAR-based pose estimation. The RAC was designed to be used in an ICP algorithm, without an initial guess at the pose. This property is, however, not robust to LIDAR measurement noise and data artefacts. The pose estimation technique described in the present work is based upon the geometric non-ambiguity criteria used originally to design the target, and is robust to the aforementioned LIDAR data characteristics. This technique has been tested using simulated point clouds representing a full range of views of the RAC. The technique has been validated using real LIDAR scans of the RAC, generated at Neptec's Ottawa facility with their Laser Camera System (LCS). Experimental results using LCS data show that pose estimates can be generated with mean errors (relative to ICP) of 1.03 [deg] and 1.08 [mm], having standard deviations of 0.56 [deg] and 0.67 [mm] respectively.

scholarly journals PARAMETRIC MODELLING APPROACH TO RECONSTRUCTING ARCHITECTURAL INDOOR SPACES FROM POINT CLOUDS

2021 ◽  
Vol XLIII-B4-2021 ◽  
pp. 251-257
Author(s):  
W. Wahbeh
Keyword(s):  
Programming Languages ◽  
Point Clouds ◽  
Visual Programming ◽  
Parametric Modelling ◽  
Architectural Practice ◽  
Industry Foundation Classes ◽  
Interior Spaces ◽  
Speed Up ◽  
Indoor Spaces ◽  
Modelling Approach

Abstract. In this paper, some outcomes of a research project which aims to introduce automation to speed up modelling of architectural spaces based on point clouds are presented. The main objective of the research is to replace some manual parametric modelling steps with automatic processes to obtain editable models in BIM-ready software and not to generate non-parametric IFC (Industry Foundation Classes) models. An approach of automation using visual programming for interior wall modelling based on point clouds is presented. The pipeline and the different concepts represented in this paper are applicable using different programming languages but here the use of Rhinoceros as a modelling software and its open-source visual programming extension "Grasshopper" is intentional as it is in common use for parametric modelling and generative design in architectural practice. In this research, it is assumed that there is a predominance of three mutually orthogonal directions of the walls in the interior spaces to be analysed, which is the case of most indoor spaces.

scholarly journals RECTIFICATION AND ROBUST MATCHING USING ORIENTED IMAGE TRIPLETS FOR MINIMALLY INVASIVE SURGERY

2016 ◽  
Vol III-3 ◽  
pp. 27-34 ◽  
Author(s):  
N. Conen ◽  
C. Jepping ◽  
T. Luhmann ◽  
H.-G. Maas
Keyword(s):  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Invasive Surgery ◽  
Current Knowledge ◽  
Point Clouds ◽  
Surface Model ◽  
Good Reliability ◽  
Camera System ◽  
Object Space ◽  
3D Measurements

Stereo endoscopes for minimally invasive surgery have been available on the market for several years and are well established in some areas. In practice, they offer a stereoscopic view to the surgeon but are not yet intended for 3D measurements. However, using current knowledge about the camera system and the difficult conditions in object space, it is possible to reconstruct a highly accurate surface model of the current endoscopic view. In particular for medical interventions, a highly reliable point cloud and real-time computation are required. To obtain good reliability, a miniaturised trinocular camera system is introduced that reduces the amount of outliers. To reduce computation time, an approach for generation of rectified image triplets and their corresponding interior and exterior camera parameters has been developed. With these modified and parameterised images it is possible to directly process 3D measurements in object space. Accordingly, an efficient semi-global optimisation is implemented by the authors. In this paper the special camera system, the rectification approach and the applied methodology of matching in rectified image triplets are explained. Finally, first results are presented. In conclusion, the trinocular camera system provides more reliable point clouds than a binocular one, especially for areas with repetitive or poor texture. Currently, the benefit of the third camera is not as great as desired.

scholarly journals A framework for non-ICP lidar-based pose estimation using an optimally constrained 3D target

2021 ◽  
Author(s):  
Pierre Saint-Cyr
Keyword(s):  
Pose Estimation ◽  
Full Range ◽  
Point Clouds ◽  
Initial Guess ◽  
Measurement Noise ◽  
Lidar Data ◽  
Lidar Measurement ◽  
Camera System ◽  
Icp Algorithm ◽  
Scan Data

This thesis describes a non-ICP-based framework fohr [sic] the computation of a pose estimate of a special target shape from raw LIDAR scan data. In previous work, an ideal unambiguously-shaped 3D target (the Reduced Ambiguity Cuboctahedron, or RAC) was designed for use in LIDAR-based pose estimation. The RAC was designed to be used in an ICP algorithm, without an initial guess at the pose. This property is, however, not robust to LIDAR measurement noise and data artefacts. The pose estimation technique described in the present work is based upon the geometric non-ambiguity criteria used originally to design the target, and is robust to the aforementioned LIDAR data characteristics. This technique has been tested using simulated point clouds representing a full range of views of the RAC. The technique has been validated using real LIDAR scans of the RAC, generated at Neptec's Ottawa facility with their Laser Camera System (LCS). Experimental results using LCS data show that pose estimates can be generated with mean errors (relative to ICP) of 1.03 [deg] and 1.08 [mm], having standard deviations of 0.56 [deg] and 0.67 [mm] respectively.

scholarly journals INDOOR MAPPING OF A COMPLEX CULTURAL HERITAGE SCENE USING TLS AND HMLS LASER SCANNING

2021 ◽  
Vol XLIII-B2-2021 ◽  
pp. 605-612
Author(s):  
V. E. Oniga ◽  
A. I. Breaban ◽  
E. I. Alexe ◽  
C. Văsii
Keyword(s):  
Standard Deviation ◽  
Cultural Heritage ◽  
Long Range ◽  
Interior Design ◽  
Point Cloud ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Point Clouds ◽  
Acquisition Time ◽  
Wide Range

Abstract. Indoor mapping and modelling is an important research subject with application in a wide range of domains including interior design, real estate, cultural heritage conservation and restoration. There are multiple sensors applicable for 3D indoor modelling, but the laser scanning technique is frequently used because of the acquisition time, detailed information and accuracy. In this paper, the efficiency of the Maptek I-Site 8820 terrestrial scanner, which is a long-range laser scanner and the accuracy of a HMLS point cloud acquired with a mobile scanner, namely GeoSlam Zeb Horizon were tested for indoor mapping. Aula Magna “Carmen Silva” of the “Gheorghe Asachi” Technical University of Iasi is studied in the current paper since the auditorium interior creates a distinct environment that combines complex geometric structures with architectural lighting and for preserving its great cultural value, the monument has a national historical significance. The registration process of the TLS point clouds was done using two methods: a semi-automatic one with artificial targets and a completely automatic one, based on Iterative Closest Point (ICP) algorithm. The resulted TLS point cloud was analysed in relation to the HMLS point cloud by computing the M3C2 (Multiscale Model to Model Cloud Comparison), obtaining a standard deviation of 2.1 cm and by investigating the Hausdorff distances from which resulted a standard deviation (σ) of 1.6 cm. Cross-sections have been extracted from the HMLS and TLS point clouds and after comparing the sections, 80% of the sigma values are less or equal to 1 cm. The results show high potential of using HMLS and also a long-range laser scanner for 3D modelling of complex scenes, the occlusion effect in the case of TLS being only 5% of the scanned area.

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