Multidimensional multiscale parser compression of 3D meshes

Akram Elkefi, Anis Meftah, M. Antonini, C. Amar
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Abstract

In this paper, we proposed two 3D mesh compression methods based on the “multidimensional multiscale parser”. The main idea of the first method is to transform the 3D object into a 2D image using the geometry image [3]. The second method is to project the wavelet transform of the object into a 2D image. The coding is processed using the MMP on these 2D images. At low bitrates, (from 0.3 to 1 bit/vertex) we have a better result in the order of 0.5 dB than the simple wavelet transform method [1]. Moreover, our method consists in processing the data progressively during acquisition while reducing considerably the memory. The problem of scan-based processing arises when compressing very large volumes of data using a minimum of memory resources. Knowing that the 3D meshes with a high degree of precision have sizes exceeding several million points, the difficulty of processing quickly arises related to this kind of data. With our scan-based method, we were able to reach levels memory even smaller than in the wavelet transform method (WT) of [1] with a better compression quality.
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三维网格多维多尺度解析器压缩
本文提出了两种基于“多维多尺度解析器”的三维网格压缩方法。第一种方法的主要思想是利用几何图像将三维物体转换成二维图像[3]。第二种方法是将目标的小波变换投影到二维图像中。在这些二维图像上使用MMP进行编码处理。在低比特率下(从0.3到1比特/顶点),我们的结果比简单的小波变换方法要好0.5 dB[1]。此外,我们的方法包括在采集过程中逐步处理数据,同时大大减少内存。当使用最少的内存资源压缩非常大量的数据时,基于扫描的处理就会出现问题。由于高精度的三维网格尺寸超过数百万点,这类数据的处理难度很快就会增加。使用基于扫描的方法,我们能够达到比[1]的小波变换方法(WT)更小的内存级别,并且具有更好的压缩质量。
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