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Geometrical vector model compressing method

A geometric model, geometric technology, applied in the field of vector geometric model compression, can solve problems such as lossy compression, complex process, etc.

Active Publication Date: 2014-05-14
西安微明电子科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Compared with the geometric compression technology, it brings great convenience to users. The most classic signal compression method is the low-pass filter compression method. This method expresses the model in multiple resolutions and uses a low-pass filter to filter Drop the high-frequency part of the model and retain its low-frequency part, but the process is relatively complicated and lossy compression

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  • Geometrical vector model compressing method
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  • Geometrical vector model compressing method

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Embodiment 1

[0076] This embodiment is to two-dimensional vector geometric model (such as figure 1 (a)) for compression, the geometric information of the two-dimensional vector geometric model is determined by the geometric signal x 2 and the geometry signal y 2 Composition, the specific method is as follows:

[0077] (1) For the two-dimensional vector geometric model: its Laplacian operator L n 1 × n 1 = 1 - 1 2 0 . . . . . . 0 ...

Embodiment 2

[0100] This embodiment is to three-dimensional vector geometric model (such as figure 2 Shown in (a)) for compression, the geometric information of the three-dimensional vector geometric model is determined by the geometric signal x 3 , geometric signal y 3 and geometric signal z 3 Composition, the method is specifically realized through the following steps:

[0101] (1) For the three-dimensional vector geometric model: its Laplacian operator Among them: A is the adjacency matrix of the three-dimensional vector geometric model, D is the vertex degree matrix of the three-dimensional vector geometric model, and where: d i is the degree of the i-th vertex of the three-dimensional vector geometric model, n 2 is the total number of vertices of the 3D vector geometric model, n 2 and i are positive integers, n 2 =34834, A and D can be determined according to the topological structure of the read model and the graph connection theory,

[0102] (2) The Laplacian operator of ...

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Abstract

The invention discloses a geometrical vector model compressing method. The geometrical vector model compressing method comprises the following steps: sampling a geometrical grid by using a random matrix, and finishing compression; restoring a sparse expression way of an original signal through a sampling signal; and restoring an original geometrical signal through an inverse Laplace operator, and further finishing decompression. The geometrical vector model compressing method can compress a geometrical vector model quickly can set a threshold according to any precision to control the effect of a restored model.

Description

technical field [0001] The invention belongs to the field of digital signal processing of computer graphics, in particular to a method for compressing vector geometric models based on the principle of rapid compression. The goal of model compression is achieved through efficient sampling technology, which has important application value in computer graphics application fields such as long-distance transmission, model maintenance, model retrieval and dimensionality reduction. Background technique [0002] With the in-depth application of computer graphics technology in computer animation, film and television games and other fields, the application of vector geometric models is more and more extensive. Data has become very easy. Users can reconstruct complex geometric models from the acquired high-precision data, and reuse existing geometric models through further processing to improve geometric design efficiency. The core of the remote transmission of vector geometric models...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04N1/41
Inventor 周明全耿国华杜卓明李康贺毅岳史哲郭竞张婧
Owner 西安微明电子科技有限公司