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Ray Space Factorization for From-Region Visibility

机译:射线空间分解以实现从区域可见性

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摘要

From-region visibility culling is considered harder than from-point visibility culling, since it is inherently four-dimensional. We present a conservative occlusion culling method based on factor-izing the 4D visibility problem into horizontal and vertical components. The visibility of the two components is solved asymmetrically: the horizontal component is based on a parameterization of the ray space, and the visibility of the vertical component is solved by incrementally merging umbrae. The technique is designed so that the horizontal and vertical operations can be efficiently realized together by modern graphics hardware. Similar to image-based from-point methods, we use an occlusion map to encode visibility; however, the image-space occlusion map is in the ray space rather than in the primal space. Our results show that the culling time and the size of the computed potentially visible set depend on the size of the viewcell. For moderate viewcells, conservative occlusion culling of large urban scenes takes less than a second, and the size of the potentially visible set is only about two times larger than the size of the exact visible set.
机译:从区域可见性剔除被认为比从点可见性剔除更困难,因为它本质上是四维的。我们提出了一种保守的遮挡剔除方法,该方法基于将4D可见性问题分解为水平和垂直分量的方法。不对称地解决了这两个分量的可见性:水平分量基于射线空间的参数化,而垂直分量的可见性则通过增量合并本影来解决。该技术经过设计,可通过现代图形硬件一起有效地实现水平和垂直操作。与基于图像的起点方法类似,我们使用遮挡图对可见性进行编码。但是,图像空间遮挡图位于射线空间而不是原始空间中。我们的结果表明,剔除时间和计算出的潜在可见集的大小取决于视单元的大小。对于中等视单元,大型城市场景的保守遮挡剔除需要不到一秒钟的时间,并且潜在可见区域的大小仅比确切可见区域的大小大两倍。

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