Determination of modeling accuracy between three-dimensional object representations

Patent metadata

Field	Value
Publication number	US-11367255-B2
Application number	US-201817052498-A
Country	US
Kind code	B2
Filing date	Oct 30, 2018
Priority date	Oct 30, 2018
Publication date	Jun 21, 2022
Grant date	Jun 21, 2022

Abstract

An example of a computer-readable medium is provided to store machine-readable instructions. The instructions may cause a processor to receive three-dimensional (3D) object representations of an object. The distance between points of a grid applied to 3D object representation and random points on the 3D object representation may provide a sampling error used in calculating a modeling accuracy between the 3D object representations.

First claim

What is claimed is:

1. A non-transitory computer-readable medium to store machine-readable instructions that, when executed by a processor, cause the processor to:
receive a first and a second three-dimensional (3D) object representation of an object;
identify a first set of grid points by application of a first grid to a surface of the first 3D object representation;
select a set of random points on the surface of the first 3D object representation;
calculate a sampling error based on a distance between the first set of grid points and the set of random points;
identify a second set of grid points by application of a second grid to a surface of the second 3D object representation;
calculate a modeling difference based on a distance between the first set of grid points and the second set of grid points; and
determine a modeling accuracy between the first and second 3D object representations based on the modeling difference and the sampling error.

2. The computer-readable medium of claim 1 , wherein the first grid includes a uniform grid in the parametric space of the first 3D object representation.

3. The computer-readable medium of claim 1 , wherein the first 3D object representation comprises a non-uniform rational basis spline (NURBS) format, and wherein the second 3D object representation comprises a Steiner Patch format.

4. The computer-readable medium of claim 1 , wherein a number of points in the first set of grid points is not equal to a number of points in the set of random points.

5. The computer-readable medium of claim 1 , wherein a distribution of the first set of grid points is based on a target precision for the second 3D object representation.

6. A non-transitory computer-readable medium to store machine-readable instructions that, when executed by a processor, cause the processor to:
receive a first three-dimensional (3D) object representation of an object, the first 3D object representation comprising a first set of surface patches, and the first set of surface patches comprising a first surface patch;
receive a second 3D object representation of the object, the second 3D object representation comprising a second set of surface patches, and the second set of surface patches comprising a second surface patch;
identify a first set of grid points by application of a first grid to a surface of the first surface patch in parametric space;
select a set of random points on the surface of the first surface patch;
calculate a sampling error based on a distance between the first set of grid points and the set of random points;
identify a second set of grid points by application of a second grid to a surface of the second surface patch in parametric space;
calculate a modeling difference based on a distance between the first set of grid points and the second set of grid points; and
determine a modeling accuracy between the first and second surface patches based on the modeling difference and the sampling error.

7. The computer-readable medium of claim 6 , wherein the machine-readable instructions, when executed by the processor, cause the processor to:
select a second set of random points on the surface of the first surface patch;
calculate a second sampling error based on a distance between the first set of grid points and the second set of random points; and
calculate a mean sampling error based on a mean of the sampling error and the second sampling error, wherein the determination of a modeling accuracy is based on the mean sampling error.

8. The computer-readable medium of claim 7 , wherein a number of points in the set of random points and a number of points in the second set of random points are different.

9. The computer-readable medium of claim 6 , wherein the first set of grid points includes a first and a second grid point, wherein the set of random points includes a first and a second random point, wherein the first random point is the point in the set of random points closest to the first grid point, wherein the second random point is the point in the set of random points closest to the second grid point, and wherein calculation of a sampling error includes calculating a distance between the first grid point and the first random point in Euclidean space and a distance between the second grid point and the second random point in Euclidean space.

10. The computer-readable medium of claim 6 , wherein the first 3D object representation comprises a non-uniform rational basis spline (NURBS) format, and wherein the second 3D object representation comprises a Steiner Patch format.

11. A method comprising:
receiving a first (3D) object representation of an object to convert into an alternative 3D object representation of the object;
converting the first 3D object representation into a second 3D object representation and a third 3D object representation;
identifying a first set of grid points by application of a first grid to a surface of the first 3D object representation;
selecting a set of random points on the surface of the first 3D object representation;
calculating a sampling error based on a distance between the first set of grid points and the set of random points;
identifying a second set of grid points by application of a second grid to a surface of the second 3D object representation;
calculating a first modeling difference based on a distance between the first set of grid points and the second set of grid points;
identifying a third set of grid points by application of a third grid to a surface of the third 3D object representation;
calculating a second modeling difference based on a distance between the first set of grid points and the third set of grid points; and
selecting the second 3D object representation as the alternative 3D object representation based on the first and second modeling differences and the sampling error.

12. The method of claim 11 , wherein selecting the second 3D object representation as the alternative 3D object representation is in response to the first modeling difference being smaller than the second modeling difference.

13. The method of claim 11 , comprising revising the second 3D object representation and the third 3D object representation based on the first and second modeling differences and the sampling error.

14. The method of claim 11 , wherein the application of the first grid to the surface of the first 3D object representation is in parametric space, wherein the application of the second grid to the surface of the second 3D object representation is in parametric space, and wherein the application of a third grid to a surface of the third 3D object representation is in parametric space.

15. The method of claim 14 , wherein first grid has a first grid spacing, wherein the second grid has a second grid spacing, wherein the third grid has a third grid spacing, and the first grid spacing, second grid spacing, and third grid spacing are the same in parametric space.

Assignees

• Hewlett Packard Development Co
• Univ Federal De Pernambuco—Ufpe

Inventors

• Henriques Diogo
• Simoes Francisco
• Melo Silvio
• Silva André
• Chaves Thiago
• Charamba Gustavo
• Teixeira Joao
• Teichrieb Veronica
• Barros Gutemberg
• Correia Walter
• Domingues Thiago
• Castilho Vinicius
• White Scott A
• Riss Marcelo

Classifications

• G06T17/30 Primary

  Polynomial surface description · CPC title

• G06T17/20

  Finite element generation, e.g. wire-frame surface description, {tesselation} · CPC title

• G06T7/0002

  Inspection of images, e.g. flaw detection · CPC title

• G06T19/00 Primary

  Manipulating three-dimensional [3D] models or images for computer graphics · CPC title

• B33Y50/00

  Data acquisition or data processing for additive manufacturing · CPC title