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The Camera Offset Space: Real-time Potentially Visible Set Computations for Streaming Rendering

delete2019-11-08
delete14
PRE
AI
J
Jozef Hladký *
H
Hans‐Peter Seidel
M
Markus Steinberger
DOI:10.1145/3355089.3356530delete
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摘要

摘要

En 中文
Potential visibility has historically always been of importance when rendering performance was insufficient. With the rise of virtual reality, rendering power may once again be insufficient, e.g., for integrated graphics of head-mounted displays. To tackle the issue of efficient potential visibility computations on modern graphics hardware, we introduce the camera offset space (COS). Opposite to how traditional visibility computations work-where one determines which pixels are covered by an object under all potential viewpoints-the COS describes under which camera movement a sample location is covered by a triangle. In this way, the COS opens up a new set of possibilities for visibility computations. By evaluating the pairwise relations of triangles in the COS, we show how to efficiently determine occluded triangles. Constructing the COS for all pixels of a rendered view leads to a complete potentially visible set (PVS) for complex scenes. By fusing triangles to larger occluders, including locations between pixel centers, and considering camera rotations, we describe an exact PVS algorithm that includes all viewing directions inside a view cell. Implementing the COS is a combination of real-time rendering and compute steps. We provide the first GPU PVS implementation that works without preprocessing, on-the-fly, on unconnected triangles. This opens the door to a new approach of rendering for virtual reality head-mounted displays and server-client settings for streaming 3D applications such as video games.
Keyword:
Visibility
Potentially Visible Set
Streaming Rendering
Virtual Reality
Real-time Rendering
GPU
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期刊

ACM Transactions on Graphics 封面图
ACM Transactions on Graphics
IF:
9.5
论文数:
4.8K
被引数:
3.6W

机构

G
Graz University of Technology
学者数:
6.7K
论文数: 6.3K
被引数: 8.5K
M
Max Planck Society
学者数:
8.2W
论文数: 7.7W
被引数: 3.3W
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