新颖的网格模型压缩算法——网格切片

针对三维(3D)网格模型的存储与网络传输问题,提出一种新颖的三维模型压缩算法。该算法基于对网格模型的切片处理,主要由以下三个步骤组成:切片顶点的计算、切片边界的均匀采样以及对切片所得图像的编码。对于一个给定的三维模型,首先,计算模型的包围盒;然后,沿包围盒长度最长的方向进行切片;同时计算切片与网格模型表面每条边的交点,构成一个多边形,这个多边形即为切片的边界;其次,对切片边界进行均匀的重采样,使每层切片具有相同的顶点数;最后,把每层的顶点坐标转化为极坐标形式,这样,所有层顶点的ρ-坐标以及θ-坐标能分别构成一张图像,原始的三维模型即能由这两张图像表示。这种表示方法具有以下两个明显的优势:第一,降低了数据的维度,有效减少了数据量;第二,具有极大的数据相关性,进一步减少了数据的熵。基于这两个优势,该算法对图像数据进行差值编码以及算术编码,最后得到压缩后的文件。与增量参数细化(IPR)方法相比,在解码模型同等质量的前提下,所提算法的编码效率提高了23%。实验结果表明,所提算法在模型存储和传输应用中能取得很好的压缩效率,有效减少了数据量。

Mesh slicer: novel algorithm for 3D mesh compression

To solve the storage and network transmission problem of the three-Dimensional (3D) mesh model, a new 3D model compression algorithm was proposed. Based on the slicing for 3D mesh, the proposed algorithm was composed of the following three steps: slice vertex calculation, slice boundary sampling and encoding for the image obtained by slicing. For a given 3D mesh model, the bounding box of the model was firstly calculated; then the model was sliced along the longest direction of the bounding box. In the procedure of slicing, the intersection point of the slice with the edge of the mesh was calculated, and as a result, all the intersection points in the same slice constituted a polygon. Then the boundary of the polygon was uniformly resampled so that each layer of the slice had the same number of vertices. After resampling of the polygon boundary, the coordinates of vertices in each slice were converted into the polar form. In this way, all ρ-coordinates and θ-coordinates of the vertices in each slice could constitute one image respectively, and the original 3D model could be represented by these two images. The new representation method has two obvious advantages: first, the dimension of the data is reduced, thus the amount of the data is effectively reduced; second, the data in these two images have great data correlation, and as a result, the entropy of the data is further reduced. Based on these two advantages, the proposed algorithm compressed these two images by difference coding technique and arithmetic coding technique, and then the compressed files were obtained. Compared with Incremental Parametric Refinement (IPR) method, the coding efficiency of the proposed algorithm was increased by 23% under the same quality of the decoded model. The experimental results show that the proposed algorithm can obtain good compression efficiency, and effectively reduce the data amount in the application of 3D model storage and transmission.