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Rate-distortion optimization for progressive compression of 3D mesh with color attributes

机译:率失真优化,可逐步压缩具有颜色属性的3D网格

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We propose a new lossless progressive compression algorithm based on rate-distortion optimization for meshes with color attributes; the quantization precision of both the geometry and the color information is adapted to each intermediate mesh during the encoding/decoding process. This quantization precision can either be optimally determined with the use of a mesh distortion measure or quasi-optimally decided based on an analysis of the mesh complexity in order to reduce the calculation time. Furthermore, we propose a new metric which estimates the geometry and color importance of each vertex during the simplification in order to faithfully preserve the feature elements. Experimental results show that our method outperforms the state-of-the-art algorithm for colored meshes and competes with the most efficient algorithms for non-colored meshes.
机译:针对色彩属性的网格,我们提出了一种基于速率失真优化的无损渐进压缩算法。在编码/解码过程中,几何形状和颜色信息的量化精度都适合每个中间网格。可以通过使用网格失真度量来最佳地确定该量化精度,或者可以基于对网格复杂度的分析来准最优地确定该量化精度,以便减少计算时间。此外,我们提出了一种新的度量,该度量可在简化过程中估算每个顶点的几何形状和颜色重要性,以便忠实地保留特征元素。实验结果表明,我们的方法优于有色网格的最新算法,并且与最有效的无色网格算法竞争。

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