Optimized occlusion culling using five-dimensional subdivision

Gotsman, Craig; Sudarsky, Oded; Fayman, Jeffrey A.

doi:10.1016/s0097-8493(99)00088-6

Cited by 31 publications

(10 citation statements)

References 21 publications

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“…A conceptually elegant idea is to shoot either random rays from a view cell [Airey et al 1990], or to first sample the boundary of the view cell with points and then sample visibility from each of these points [Levoy and Hanrahan 1996]. Recent algorithms try to address the question on how to best position new samples based on visibility information from previous samples [Gotsman et al 1999;Pito 1999;Wilson and Manocha 2003;Nirenstein and Blake 2004;Wonka et al 2006].…”

Section: Related Workmentioning

confidence: 99%

Adaptive global visibility sampling

Bittner

Mattausch

Wonka

et al. 2009

ACM SIGGRAPH 2009 Papers

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In this paper we propose a global visibility algorithm which computes from-region visibility for all view cells simultaneously in a progressive manner. We cast rays to sample visibility interactions and use the information carried by a ray for all view cells it intersects. The main contribution of the paper is a set of adaptive sampling strategies based on ray mutations that exploit the spatial coherence of visibility. Our method achieves more than an order of magnitude speedup compared to per-view cell sampling. This provides a practical solution to visibility preprocessing and also enables a new type of interactive visibility analysis application, where it is possible to quickly inspect and modify a coarse global visibility solution that is constantly refined.

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Section: Related Workmentioning

confidence: 99%

Adaptive global visibility sampling

Bittner

Mattausch

Wonka

et al. 2009

ACM SIGGRAPH 2009 Papers

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“…For precomputed visibility, the size of the data stored for the view cells may become so large that the total size of the PVSs is much larger than the size of the scene. Aside from a few studies [23], [25], the problem of big PVS storage problem has not been given enough importance [6].…”

Section: Benefits Of Slicingmentioning

confidence: 99%

Conservative occlusion culling for urban visualization using a slice-wise data structure

Yılmaz

Güdükbay

2007

Graphical Models

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Fig. 1. An occlusion culling algorithm using our slice-wise data structure sends approximately 54 % fewer triangles to the graphics pipeline and increases frame rate by 46 %, as compared to an occlusion culling algorithm using building-level granularity of visibility in this 1.5M-triangle environment. The red colored sections show occluded regions, which are discarded from the graphics pipeline. In addition, the data structure decreases Potentially Visible Set (PVS) storage requirement drastically. AbstractIn this paper, we propose a new shrinking process for conservative from-point occlusion culling algorithms and a data structure for the visualization of urban environments. The visible geometry in a typical urban walkthrough mainly consists of partially visible buildings. Occlusion-culling algorithms, in which the granularity is based on buildings, render these partially visible buildings completely. We observe that the visibility in urban walkthroughs shows certain characteristics. The proposed slice-wise data structure represents the buildings, exploiting these characteristics, in terms of slices parallel to the coordinate axes. This forms the base for occlusion culling where the occlusion granularity is at slice level. The proposed slice-wise data structure has minimal storage requirements. The visible parts can be accessed at constant time during navigation with the help of a preprocessing stage. We also propose to shrink the occluders in a scene. This is necessary for a conservative from-point occlusion culling algorithm, which can also be applied to nonconvex general 3D occluders. Empirical results show that a 54 % decrease in the number of processed polygons and 46 % speed-up in frame-rate can be achieved by using the proposed conservative occlusion-culling algorithm with rather than an occlusion-culling method where the granularity is based on individual buildings.

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“…However, there are several methods which create view cells during the PVS computation. Gotsman et al [6] construct a 5D subdivision of view space in which they use sampled visibility to evaluate the efficiency of the candidate splitting planes. The visibility octree of Saona-Vázquez et al [17] is constructed by a view space subdivision which terminates when reaching a predefined triangle budget or when visibility cannot be reduced by the associated conservative algorithm.…”

Section: View Space Subdivisionmentioning

confidence: 99%

Optimized subdivisions for preprocessed visibility

Mattausch

Bittner

Wonka

et al. 2007

Proceedings of Graphics Interface 2007 on - GI '07

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This paper describes a new tool for preprocessed visibility. It puts together view space and object space partitioning in order to control the render cost and memory cost of the visibility description generated by a visibility solver. The presented method progressively refines view space and object space subdivisions while minimizing the associated render and memory costs. Contrary to previous techniques, both subdivisions are driven by actual visibility information. We show that treating view space and object space together provides a powerful method for controlling the efficiency of the resulting visibility data structures.

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Optimized occlusion culling using five-dimensional subdivision

Cited by 31 publications

References 21 publications

Adaptive global visibility sampling

Adaptive global visibility sampling

Conservative occlusion culling for urban visualization using a slice-wise data structure

Optimized subdivisions for preprocessed visibility

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