Compression of a three-dimensional modeled object

• US 9,972,129 B2
• Filed: 10/31/2016
• Issued: 05/15/2018
• Est. Priority Date: 10/30/2015
• Status: Active Grant

• Current Assignee: Dassault Systemes SA
• Original Assignee: Dassault Systemes SA
• Inventors: Michel, Fabrice, Boulkenafed, Malika
• Primary Examiner(s): Hoang, Phi
• Application Number:
  US15/339,676
• Publication Number:
  US 20170124761A1
• Time in Patent Office: 561 Days
• CPC Class Codes: G06T 17/20 Finite element generation, e.g. wire-frame surface description, tesselation
• CPC Class Codes: G06T 2200/04 involving 3D image data
• CPC Class Codes: G06T 2207/20021 Dividing image into blocks, subimages or windows
• CPC Class Codes: G06T 3/20 Linear translation of whole images or parts thereof, e.g. panning
• CPC Class Codes: G06T 3/40 Scaling of whole images or parts thereof, e.g. expanding or contracting
• CPC Class Codes: G06T 9/00 Image coding bandwidth or redundancy reduction for static pictures H04N1/41; coding or decoding of static colour picture signals H04N1/64; methods or arrangements for coding, decoding, compressing or decompressing digital video signals H04N19/00

Abstract

The invention notably relates to a computer-implemented method for compressing a three-dimensional modeled object. The method comprises providing a mesh of a three-dimensional modeled object, parameterizing (u,v) the mesh on a two-dimensional plane, converting the parameterized mesh into an image I, defining a grid of cells from the image I, each cell being defined by a set of control points, computing a relevance of each cell of the grid, determining at least one cell having a relevance lower than a pre-determined threshold, resizing the at least one determined cell and computing a resulting grid, computing a transformation for each pixel of the image from the resulting grid, and applying the computed transformation to the image I.

Claims

1. A computer-implemented method for compressing a three-dimensional modeled object, comprising:

providing a mesh of a three-dimensional modeled object;

parameterizing (u,v) the mesh on a two-dimensional plane;

converting the parameterized mesh into an image I;

defining a grid of cells from the image I, each cell being defined by a set of control points;

computing a relevance of each cell of the grid;

determining at least one cell having a relevance lower than a pre-determined threshold;

resizing the at least one determined cell and computing a resulting grid;

computing a transformation for each pixel of the image from the resulting grid; and

applying the computed transformation to the image I.

2. The computer-implemented method of claim 1, wherein the determination of the said at least one cell having a relevance lower than a pre-determined threshold comprises the determination of a set of one or more cells having the lowest relevance.

3. The computer-implemented method of claim 1, further comprising:

providing an image significance by computing a significance of each pixel in the image I;

extracting an original spatial domain (Ω

) of the Significance Image;

providing a transformation T_θ

, parameterized as an interpolating spline by a set of control points, from the original spatial domain (Ω

) to a resized spatial domain (Ω

′

),

wherein defining a grid of cells from the image I comprises subdividing the original spatial domain (Ω

) into cells, each cell being defined by a subset of control points of the set,

wherein computing a relevance of each cell of the grid comprises computing, for each cell, a weighted average of the significance of the pixels in the cell, the weighted average being computed using the interpolating spline, and

wherein computing a transformation for each pixel of the image I from the resulting grid comprises computing the transformation T_θ

over a spatial domain of the image I obtained by the conversion of the parameterized mesh from the resulting grid.

4. The computer-implemented method of claim 3, wherein the transformation T_θ

is parameterized as a free form deformation interpolating spline,

wherein displacement function u_θ

(x) is defined by the equation

5. The computer-implemented method of claim 3, wherein the computation of the significance of each pixel is carried out with the function

SI=α

E_geom+(1−

α

)E_norm

where α

ϵ

[0;

1],

where

6. The computer-implemented method of claim 5, wherein the computation of the significance of each pixel further comprises:

selecting, upon user action, two or more vertices of the mesh;

translating the user selection into a chart of vertices; and

setting the coefficient α

=0 to minimize the significance of the pixels of the image I linked to the vertices of the chart.

7. The computer-implemented method of claim 5, wherein the computation of the significance of each pixel further comprises:

selecting, upon user action, two or more vertices of the mesh;

translating the user selection into a chart of vertices; and

setting the coefficient α

=1 to maximize the significance of the pixels of the image I linked to the vertices of the chart.

8. The computer-implemented method of claim 1, wherein the steps of defining a grid of cells from the image I, computing a relevance of each cell of the grid, determining at least one cell having a relevance lower than a pre-determined threshold, resizing the at least one determined cell and computing a resulting grid, computing a transformation for each pixel of the image from the resulting grid, and applying the computed transformation to the image I are iterated until the computed transformation to the image I satisfied a compression criteria.

9. The computer-implemented method of claim 8, wherein the iteration stops when at least one of the following criteria is reached:

no more cell of the grid has a relevance lower than the pre-determined threshold;

a compression rate of a new image J obtained by applying the computed transformation to the image I, reaches a given threshold; and

a number of pixels of a new image J obtained by applying the computed transformation to the image I, reaches a given value threshold.

10. The computer-implemented method of claim 8, wherein the number of control points of the set is increased for each iteration.

11. The computer-implemented method of claim 1, wherein resizing the at least one determined cell comprises reducing the at least one determined cell, wherein the reduction of the at least one determined cell is performed by:

bringing closer to vertices of the said at least one determined cell, all vertices to the left and to the right of the cell; and

bringing closer to the vertices of the said at least one determined cell, all vertices to the top and to the bottom of the cell.

12. The computer-implemented method of claim 1, further comprising building a three-dimensional modeled object from a new image J obtained by applying the computed transformation to the image I.

13. The computer-implemented method of claim 1, wherein resizing the at least one determined cell and computing a resulting grid is carried out regardless keeping straight the edges of the image I.

14. A non-transitory computer medium having stored thereon a program comprising instructions for performing computer-implemented method for compressing a three-dimensional modeled object, the method comprising:

providing a mesh of a three-dimensional modeled object;

parameterizing (u,v) the mesh on a two-dimensional plane;

converting the parameterized mesh into an image I;

defining a grid of cells from the image I, each cell being defined by a set of control points;

computing a relevance of each cell of the grid;

determining at least one cell having a relevance lower than a pre-determined threshold;

resizing the at least one determined cell and computing a resulting grid;

computing a transformation for each pixel of the image from the resulting grid; and

applying the computed transformation to the image I.

15. A system comprising:

a memory; and

processing circuitry coupled to the memory,

wherein the memory has recorded a computer program for performing computer-implemented method for compressing a three-dimensional modeled object, the method comprising;

providing a mesh of a three-dimensional modeled object;

parameterizing (u,v) the mesh on a two-dimensional plane;

converting the parameterized mesh into an image I;

defining a grid of cells from the image I, each cell being defined by a set of control points;

computing a relevance of each cell of the grid;

determining at least one cell having a relevance lower than a pre-determined threshold;

resizing the at least one determined cell and computing a resulting grid;

computing a transformation for each pixel of the image from the resulting grid; and

applying the computed transformation to the image I.