3D Surface Reconstruction from Scattered Data Points Using a Set of Curves on a Three Dimensional Space

2002 ◽  
Author(s):  
Faten Chaieb ◽  
Faouzi Ghorbel
Keyword(s):  
Surface Reconstruction ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Scattered Data ◽  
3D Surface Reconstruction ◽  
3D Surface ◽  
Data Points ◽  
Three Dimensional Space

Surface Reconstruction of In Vivo Geometry Based on Medical Images Using Multilevel Radial Basis Functions

2004 ◽  
Author(s):  
Yoke Kong Kuan ◽  
Paul F. Fischer ◽  
Francis Loth
Keyword(s):  
Radial Basis Functions ◽  
Surface Reconstruction ◽  
Medical Images ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Basis Functions ◽  
Radial Basis ◽  
Point Set ◽  
Three Dimensional Space

Compactly supported radial basis functions (RBFs) were used for surface reconstruction of in vivo geometry, translated from two dimensional (2D) medical images. RBFs provide a flexible approach to interpolation and approximation for problems featuring unstructured data in three-dimensional space. Point-set data are obtained from the contour of segmented 2-D slices. Multilevel RBFs allow smoothing and fill in missing data of the original geometry while maintaining the overall structure shape.

scholarly journals Study on Reconstruction and Feature Tracking of Silicone Heart 3D Surface

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7570
Author(s):  
Ziyan Zhang ◽  
Yan Liu ◽  
Jiawei Tian ◽  
Shan Liu ◽  
Bo Yang ◽  
...  
Keyword(s):  
Surface Reconstruction ◽  
Feature Tracking ◽  
Feature Matching ◽  
Negative Impact ◽  
Three Dimensional ◽  
Geometric Constraints ◽  
Feature Point ◽  
Feature Points ◽  
3D Surface Reconstruction ◽  
3D Surface

At present, feature-based 3D reconstruction and tracking technology is widely applied in the medical field. In minimally invasive surgery, the surgeon can achieve three-dimensional reconstruction through the images obtained by the endoscope in the human body, restore the three-dimensional scene of the area to be operated on, and track the motion of the soft tissue surface. This enables doctors to have a clearer understanding of the location depth of the surgical area, greatly reducing the negative impact of 2D image defects and ensuring smooth operation. In this study, firstly, the 3D coordinates of each feature point are calculated by using the parameters of the parallel binocular endoscope and the spatial geometric constraints. At the same time, the discrete feature points are divided into multiple triangles using the Delaunay triangulation method. Then, the 3D coordinates of feature points and the division results of each triangle are combined to complete the 3D surface reconstruction. Combined with the feature matching method based on convolutional neural network, feature tracking is realized by calculating the three-dimensional coordinate changes of the same feature point in different frames. Finally, experiments are carried out on the endoscope image to complete the 3D surface reconstruction and feature tracking.

A New Reverse Engineering Method for the 3D Surface Reconstruction without Contact

2015 ◽  
Vol 1099 ◽  
pp. 140-146
Author(s):  
L. Giraud-Moreau ◽  
R. Slysz ◽  
H. Borouchaki
Keyword(s):  
Reverse Engineering ◽  
Pattern Matching ◽  
Surface Reconstruction ◽  
Delaunay Triangulation ◽  
Three Dimensional ◽  
Engineering Method ◽  
Two Dimensional ◽  
3D Surface Reconstruction ◽  
3D Surface ◽  
Structure Light

In this paper, a new reverse engineering method is proposed for 3d surface reconstruction without contact. This method is based on the combination of stereovision and structure light methods. The originality of the proposed technique is that the pattern is a two-dimensional Delaunay triangulation. A key characterizing the vertices is computed for each vertex. The pattern matching between two images is reduced to the comparison of two meshes. The three dimensional triangulation of the surface can then be obtained by using the geometric properties of the acquisition devices.

The Curve-Mesh Concept in Reconstructing Smooth Surface From Noisy Data

1990 ◽  
Author(s):  
P. D. Kaklis
Keyword(s):  
Dimensional Space ◽  
Three Dimensional ◽  
Test Function ◽  
Statistical Framework ◽  
Continuous Surface ◽  
Data Points ◽  
Constrained Minimization Problem ◽  
Numerical Performance ◽  
Newton Raphson ◽  
Three Dimensional Space

Abstract This paper is concerned with the problem of filtering the noise encountered in the measurements taken from a smooth (GC2-continuous) surface in the three-dimensional space. For this purpose, the data points are firstly considered to belong to a three-dimensional entity which is drastically simpler than a surface, namely the noisy curvature-continuous quadrilateral curve-mesh connecting the data points. The curve-mesh concept, apparently introduced by Hosaka (1969), is then combined with the concept of fairing in a statistical framework introduced by Reinsen (1967; 1971), yielding a constrained minimization problem for the fairing curve-mesh. After establishing that this problem has a unique solution in an appropriate Hilbert space, a convergent Newton-Raphson-type algorithm for constructing it in a cubic-spline subspace is presented in detail. Finally, the numerical performance of this algorithm in the context of a Monte-Carlo experimentation with the so-called Franke’s principal test function (1979,1980,1982) is discussed.

Assessing Circularity in Three Dimensions1

2000 ◽  
Vol 123 (1) ◽  
pp. 128-134 ◽  
Author(s):  
Shuo-Yan Chou ◽  
Shih-Wei Lin ◽  
Chien-Hong Chen
Keyword(s):  
Cross Section ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Two Dimensional ◽  
Coordinate Measuring Machines ◽  
Single Plane ◽  
Research Designs ◽  
Data Points ◽  
Three Dimensional Space ◽  
Assessment Results

This research resolves an inconsistency problem that arises from assessing circularity of workpiece measured by coordinate measuring machines (CMMs). Although the notion of circularity is employed to constrain two-dimensional circular features, in practice the measured points are obtained in a three-dimensional space and are in general not in the same plane, let alone being in a “perpendicular” cross-section. All of the algorithms currently used for assessing circularity deal with data in a single plane that is perpendicular to the axis of a cylindrical feature from which the circular feature is extracted. This discrepancy causes the assessed circularity significantly departing from the actual circularity and resulting in rejection of in-tolerance parts. This research designs a compensation procedure for deriving two-dimensional data from three-dimensional biased measured points. The circularity is assessed based on the compensated two-dimensional data points. The assessment results with the compensation are compared with those without compensation. A program containing a variety of implementations of form fitting algorithms is developed and used to illustrate the improvement on the accuracy of assessment.

Extension of the Spatial PDI Model to Three Dimensions

1997 ◽  
Vol 84 (1) ◽  
pp. 176-178
Author(s):  
Frank O'Brien
Keyword(s):  
Population Density ◽  
Dimensional Space ◽  
Finite Lattice ◽  
Three Dimensional ◽  
Upper Bounds ◽  
Three Dimensions ◽  
Lower And Upper Bounds ◽  
Density Index ◽  
Three Dimensional Space

The author's population density index ( PDI) model is extended to three-dimensional distributions. A derived formula is presented that allows for the calculation of the lower and upper bounds of density in three-dimensional space for any finite lattice.

A Peptoid with Extended Shape in Water

2019 ◽  
Author(s):  
Jumpei Morimoto ◽  
Yasuhiro Fukuda ◽  
Takumu Watanabe ◽  
Daisuke Kuroda ◽  
Kouhei Tsumoto ◽  
...  
Keyword(s):  
Spectroscopic Analysis ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Biomolecular Recognition ◽  
Biological Application ◽  
New Class ◽  
Proteolytic Resistance ◽  
Pharmacokinetic Properties ◽  
Optically Pure ◽  
Three Dimensional Space

<div> <div> <div> <p>“Peptoids” was proposed, over decades ago, as a term describing analogs of peptides that exhibit better physicochemical and pharmacokinetic properties than peptides. Oligo-(N-substituted glycines) (oligo-NSG) was previously proposed as a peptoid due to its high proteolytic resistance and membrane permeability. However, oligo-NSG is conformationally flexible and is difficult to achieve a defined shape in water. This conformational flexibility is severely limiting biological application of oligo-NSG. Here, we propose oligo-(N-substituted alanines) (oligo-NSA) as a new peptoid that forms a defined shape in water. A synthetic method established in this study enabled the first isolation and conformational study of optically pure oligo-NSA. Computational simulations, crystallographic studies and spectroscopic analysis demonstrated the well-defined extended shape of oligo-NSA realized by backbone steric effects. The new class of peptoid achieves the constrained conformation without any assistance of N-substituents and serves as an ideal scaffold for displaying functional groups in well-defined three-dimensional space, which leads to effective biomolecular recognition. </p> </div> </div> </div>

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