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3 Method and Apparatus for compressing vertex position of 3D mesh model

机译:3压缩3D网格模型顶点位置的方法和装置

摘要

The invention relates to a method and apparatus for three-dimensional vertex position (vertex position) data indicating the coordinates on the three-dimensional space of the information used to present a mesh model by using the compression of the second quantization step.; Conventional compression methods occurs when the residual error is very large and the quantization error greatly in this case, is the shape of the reconstructed three-dimensional model to be visually very distorted or deformed, and do lowered away from the entropy encoding operation efficiency compression there was. Compression top position of a three-dimensional mesh model method according to the invention made in view of solving the above problems is characterized in that the compression method applied to the vertex position encoder and the decoder of a 3D mesh model, constituting the 3D mesh model a first step of receiving input to the vertex position information for determining a first quantization step and the second quantization step used in the quantization process, and a single 2; A second step of predicting the current position from the previous vertex to the vertex location encoding; A third step of comparing the predicted peak position and the actual peak position to obtain the prediction error of the peak position; A fourth step of compression by quantizing the prediction error of the peak position in the first quantization step; And a fifth step of compression by quantizing the first quantization error that occurred after the first quantizer with a secondary quantization step.
机译:本发明涉及用于通过利用第二量化步骤的压缩来表示表示用于表示网格模型的信息的三维空间上的坐标的三维顶点位置(vertex position)数据的方法和设备;在这种情况下,当残留误差非常大且量化误差很大时,就会出现传统的压缩方法,这种重建方法是重构的三维模型的形状在视觉上非常失真或变形,并且从那里的熵编码运算效率压缩开始降低是。鉴于解决上述问题而做出的根据本发明的三维网格模型方法的压缩顶部位置的特征在于,应用于构成3D网格模型的3D网格模型的顶点位置编码器和解码器的压缩方法接收到顶点位置信息的输入以确定量化处理中使用的第一量化步骤和第二量化步骤的第一步,以及单个2;预测从先前顶点到顶点位置编码的当前位置的第二步;第三步,比较预测的峰值位置和实际的峰值位置,得到峰值位置的预测误差;第四压缩步骤,通过在第一量化步骤中量化峰值位置的预测误差;以及第五步骤,通过利用次级量化步骤对在第一量化器之后发生的第一量化误差进行量化来进行压缩。

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