A Fast Parallel Adaptive Simplification Method Based on Vertex Clustering for External Memory Model

Abstract

The invention provides a quick parallel self-adaptive simplification method based on vertex clustering for an out-of-core model. The method comprises the steps that partition and communication are carried out; clustering and mapping are carried out; vertexes contained in a surface patch are obtained; the normal vector of a global vertex, coefficients of a, b, c and d of a plane equation and the mid value of side length are calculated; parallel sorting is carried out; surface patches to which all vertexes belong are obtained; and the serial numbers of the vertexes are updated. The quick parallel self-adaptive simplification method firstly realizes the quick simplification of the out-of-core model; secondly, the executing process of the simplification can be remarkably accelerated; and finally, the topology and geometrical models of the out-of-core model can be effectively maintained, and the self-adaptive simplification based on sight point is realized.

Description

technical field [0001] The invention relates to the field of computer graphics, in particular to a fast parallel self-adaptive simplification method based on vertex clustering of an external memory model. Background technique [0002] With the rapid development of technologies such as digital geometric modeling of 3D scanners, triangular mesh models have been widely used in many fields such as reverse engineering, virtual reality, and 3D animation. At the same time, with the improvement of modeling precision and object complexity, the amount of triangular mesh data generated is also increasing, often requiring millions of triangular patches to accurately describe the detailed features of the object surface. These huge amounts of data have brought enormous pressure to computer storage, analysis, display and network transmission. However, in many cases, a high-resolution model is not always necessary, and there is a compromise between model accuracy and processing time. There...

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Problems solved by technology

[0005] Since 1993, although many scholars have proposed a variety of different improvement methods to improve the simplification performance of the vertex clustering algorithm, due to the main factors of the inability to maintain the initial model topology, the difficulty of simplifying the scale control, and the poor quality of the simplification results, The algorithm never progressed to the more general attention that edge-folding methods have

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