Abstract

A method of lossless geometry compression on the coordinates of the vertexes for grid model is presented. First, the 3D coordinates are pre-processed to be transformed into a specific form. Then these 3D coordinates are changed into 1D data by making the three coordinates of a vertex represented by only a position number, which is made of a large integer. To minimize the integers, they are sorted and the differences between two adjacent vertexes are stored in a vertex table. In addition to the technique of geometry compression on coordinates, an improved method for storing the compressed topological data in a facet table is proposed to make the method more complete and efficient. The experimental results show that the proposed method has a better compression rate than the latest method of lossless geometry compression, the Isenburg-Lindstrom-Snoeyink method. The theoretical analysis and the experiment results also show that the important decompression time of the new method is short. Though the new method is explained in the case of a triangular grid, it can also be used in other forms of grid model.

Highlights

  • The triangular mesh provides one of the most popular representation for 3D graphic models

  • We explore a new method for the lossless compression of geometry

  • The proposed method is described on the triangular facet grid model, the basic idea can be used for compressing other grid models

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Summary

Introduction

The triangular mesh provides one of the most popular representation for 3D graphic models. Nsygs,t.L,in2g0h1u3a, VLioal.n1d0B, o3r0u8t:Ž2a0l1ik3: 1 Lossless Geometry Compression Through Changing 3D Coordinates into 1D world objects. These techniques generate huge volumes of 3D object geometry data. The need for more compact mesh representations has motivated researchers to develop techniques for the compression of connectivity [1,2,3,4], geometry [5,6,7,8] and properties [9,10,11,12]. In the literature [13], a method is described for the compression of a floating‐point coordinate with predictive coding in a lossless manner. The new method is explained in the case of a triangle grid, it can be used in other grids

Change Three Dimensional Coordinates into One Dimension
Organization of the Facet Table
Optimization of the Compression Method
Experiment Result and Analysis
Conclusion
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