Model simplification method and related equipment thereof

A model simplification and model simplification technology, applied in the field of data processing, can solve the problems of long time consumption, large resource consumption, high resource demand, etc., and achieve the effect of improving simplification effect and processing effect

Pending Publication Date: 2022-01-18
NEUSOFT CORP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] In fact, in order to improve the authenticity of the model display effect, some high-dimensional data models with relatively complex structures are usually built with the help of a large number of data points, so that a large amount of resources (such as computing resources) are consume...

Method used

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  • Model simplification method and related equipment thereof
  • Model simplification method and related equipment thereof
  • Model simplification method and related equipment thereof

Examples

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example 1

[0172] Example 1, when the above "at least one adjacent point of the vertex to be used" includes M adjacent points, and the relative position representation data between the mth adjacent point and the reference adjacent surface includes the distance between the mth adjacent point and the reference adjacent surface Distance, m is a positive integer, when m≤M, step 52 may specifically include: performing a first statistical analysis process on the distance from the first adjacent point to the reference adjacent surface to the distance from the Mth adjacent point to the reference adjacent surface , to obtain the curvature characterization data of the vertex to be used.

[0173] Wherein, "the first statistical analysis processing" can be preset, for example, it can specifically be to carry out summation processing (as shown in formula (5)), also can be to carry out average value processing, can also be to obtain maximum value processing Wait.

[0174]

[0175] In the formula, ...

example 2

[0177] Example 2, when the above "at least one adjacent point of the vertex to be used" includes M adjacent points, and the relative position representation data between the mth adjacent point and the reference adjacent surface includes the mth adjacent point to the reference adjacent surface The distance of the preset position, m is a positive integer, and when m≤M, step 52 may specifically include: presetting the distance from the first adjacent point to the preset position on the reference adjacent surface to the Mth adjacent point to the reference adjacent surface Set the distance of the position to perform the second statistical analysis process to obtain the curvature characterization data of the vertex to be used.

[0178] Wherein, "the second statistical analysis processing" can be preset, for example, it can specifically be to perform summation processing (as shown in formula (6)), also can be to carry out average value processing, can also be to obtain maximum value p...

example 3

[0182] Example 3, when the above "at least one adjacent point of the vertex to be used" includes M adjacent points, and the relative position representation data between the mth adjacent point and the reference adjacent surface includes the distance between the mth adjacent point and the reference adjacent surface distance, and the distance from the mth adjacent point to the preset position on the reference adjacent surface, m is a positive integer, and when m≤M, step 52 may specifically include step 521-step 522:

[0183] Step 521: Determine the curvature contribution value of the mth adjacent point according to the ratio between the distance from the mth adjacent point to the reference adjacent surface and the distance from the mth adjacent point to a preset position on the reference adjacent surface. Wherein, m is a positive integer, m≤M, and M is a positive integer.

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Abstract

The embodiment of the invention discloses a model simplification method and related equipment thereof. The method comprises the steps: firstly determining a quadratic error matrix and curvature representation data of at least one vertex in a to-be-simplified model after the to-be-simplified model is obtained; respectively determining a quadratic error matrix and curvature representation data of at least one vertex pair according to the quadratic error matrixes and curvature representation data of the vertexes; then, according to the quadratic error matrixes of the vertex pairs and curvature representation data, the merging cost of the vertex pairs is determined; and finally, according to the combination cost of the vertex pairs, performing vertex combination processing on the to-be-simplified model, so that the number of vertexes in the to-be-simplified model obtained through vertex combination processing is less than the number of vertexes in the original to-be-simplified model. Therefore, less resources are consumed when subsequent model processing is carried out on the to-be-simplified model obtained through vertex merging processing, and the processing effect on the high-dimensional data model can be improved.

Description

technical field [0001] The present application relates to the technical field of data processing, in particular to a model simplification method and related equipment. Background technique [0002] With the continuous popularization of some computer technologies (eg, augmented reality technology, virtual reality technology, mixed reality technology, etc.), high-dimensional data models (eg, three-dimensional data models) are more and more widely used. [0003] In fact, in order to improve the authenticity of the model display effect, some high-dimensional data models with relatively complex structures are usually built with the help of a large number of data points, so that a large amount of resources (such as computing resources) are consumed during the processing of these high-dimensional data models , memory resources, etc.), so that the processing effect of these high-dimensional data models is relatively poor (for example, the processing process takes too long, the resou...

Claims

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Application Information

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IPC IPC(8): G06T17/20G06T7/64
CPCG06T17/205G06T7/64
Inventor 邓聪
Owner NEUSOFT CORP
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