Model simplification method and related equipment thereof

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...

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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 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 resource requirements of the processing process are too high, etc.)

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