IEEE Trans Vis Comput Graph. 2018 May;24(5):1705-1716. doi: 10.1109/TVCG.2017.2695182. Epub 2017 Apr 18.
Most graphics hardware features memory to store textures and vertex data for rendering. However, because of the irreversible trend of increasing complexity of scenes, rendering a scene can easily reach the limit of memory resources. Thus, vertex data are preferably compressed, with a requirement that they can be decompressed during rendering. In this paper, we present a novel method to exploit existing hardware texture compression circuits to facilitate the decompression of vertex data in graphics processing unit (GPUs). This built-in hardware allows real-time, random-order decoding of data. However, vertex data must be packed into textures, and careless packing arrangements can easily disrupt data coherence. Hence, we propose an optimization approach for the best vertex data permutation that minimizes compression error. All of these result in fast and high-quality vertex data decompression for real-time rendering. To further improve the visual quality, we introduce vertex clustering to reduce the dynamic range of data during quantization. Our experiments demonstrate the effectiveness of our method for various vertex data of 3D models during rendering with the advantages of a minimized memory footprint and high frame rate.
大多数图形硬件都具有存储纹理和顶点数据以进行渲染的内存。然而,由于场景复杂性不断增加的不可逆转趋势,渲染场景很容易达到内存资源的限制。因此,最好对顶点数据进行压缩,并要求在渲染过程中可以对其进行解压。在本文中,我们提出了一种利用现有硬件纹理压缩电路来促进图形处理单元(GPU)中顶点数据解压的新方法。这种内置硬件允许实时、随机顺序地解码数据。然而,顶点数据必须打包到纹理中,如果包装安排不当,很容易破坏数据一致性。因此,我们提出了一种优化方法,用于对顶点数据进行最佳排序,以最小化压缩误差。所有这些都实现了实时渲染的快速和高质量顶点数据解压。为了进一步提高视觉质量,我们引入了顶点聚类来减少量化过程中的数据动态范围。我们的实验表明,我们的方法在渲染各种 3D 模型的顶点数据时非常有效,具有占用内存小和帧率高的优点。