Mean quadratic error measuring method

Abstract

The invention relates to the field of computer graphics, and discloses a mean quadratic error measuring method. The mean quadratic error measuring method comprises the steps that all vertexes in a model are collected, and the vectors of all triangular faces are updated; according to the specific steps, a vertex error is defined as the sum of the squares of the distances between the vertexes and all the triangular faces adjacent to the vertexes according to a QEM algorithm; calculation of the vertex error is transferred o a GPU end; a pixel value is defined, and a row vector is converted into the pixel value and placed in Color Buffer; the pixel value is acquired from the Color Buffer and is reverted to a mean quadratic error matrix; the computational formula of the second order error can be obtained according to the computational formula of the vertex error. The mean quadratic error measuring method is provided, the QEM algorithm is adopted, calculation of the vertex error is transferred to the GPU end, the pixel value is acquired from the Color Buffer and reverted to the mean quadratic error matrix, and time needed in the initialization stage of second order error measurement is greatly shortened.

Description

technical field [0001] The invention relates to the field of receiver graphics, in particular to an average quadratic error measurement method. Background technique [0002] With the development of 3D scanning technology, 3D models with tens of thousands or even millions of vertices have become more common, and such model data has brought enormous pressure to the storage, rendering and transmission of computer systems, especially it is difficult to meet real-time rendering requirements. requirements. Model simplification is a key technology to solve these problems. [0003] Garland et al. proposed in 1997 that the edge contraction simplification algorithm based on QEM (Quadric Error Metrics) is a model simplification algorithm that has performed very well in terms of comprehensive performance so far. The QEM edge shrinkage simplification algorithm first needs to calculate the quadratic error matrix of each vertex, then select all appropriate vertex pairs, calculate the shr...

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Problems solved by technology

[0005] The present invention aims at the shortcomings of the QEM edge contraction simplification algorithm in the prior art that the initialization time is long and the time-consuming operation of the initialization stage is to calculate the secondary error matrix of the vertices, and provides a method that can greatly shorten the time required for the initialization stage in the secondary error measurement. Time-consuming average quadratic error measure

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