Efficient image-based methods for rendering soft shadows

Agrawala, Maneesh; Ramamoorthi, Ravi; Heirich, Alan; Moll, Laurent

doi:10.1145/344779.344954

Cited by 86 publications

(74 citation statements)

References 26 publications

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“…Thus, we must use warping and boundary flooding in scanline algorithms. It is interesting to note that this corresponds closely to the approach of [Agrawala et al 2000]. Table 1).…”

Section: Correctness Analysis (Scanline Vs Grid)supporting

confidence: 76%

“…Thus, in our method, we trace all primary eye-rays and cull only shadow-rays, whenever possible. Our method is closest to that of [Agrawala et al 2000], who exploited coherence in the visibility of an area light source to reduce the number of shadow-rays cast. We adapt their method to environment maps, and show that modifications to both the spatial sharing and angular sharing of visibility information are required for accurate and efficient visibility sampling in the context of environment lighting.…”

Section: Introductionmentioning

confidence: 99%

“…[ Agrawala et al 2000] achieve their speedup by assuming that visibility of the light source is similar for adjacent pixels. They determine visibility of regularly spaced samples of the area light source, and then share that visibility information with the subsequent pixel of the scanline order.…”

Section: Introductionmentioning

confidence: 99%

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Efficient Shadows for Sampled Environment Maps

Ben-Artzi

Ramamoorthi

Agrawala

2006

Journal of Graphics Tools

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This paper addresses the problem of efficiently calculating shadows from environment maps in the context of ray-tracing. Since accurate rendering of shadows from environment maps requires hundreds of lights, the expensive computation is determining visibility from each pixel to each light direction. We show that coherence in both spatial and angular domains can be used to reduce the number of shadow-rays that need to be traced. Specifically, we use a coarseto-fine evaluation of the image, predicting visibility by reusing visibility calculations from 4 nearby pixels that have already been evaluated. This simple method allows us to explicitly mark regions of uncertainty in the prediction. By only tracing rays in these and neighboring directions, we are able to reduce the number of shadow-rays traced by up to a factor of 20 while maintaining error rates below 0.01%. For many scenes, our algorithm can add shadowing from hundreds of lights at only twice the cost of rendering without shadows. Sample source code is available online. [Agarwal et al. 2003].

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“…Thus, we must use warping and boundary flooding in scanline algorithms. It is interesting to note that this corresponds closely to the approach of [Agrawala et al 2000]. Table 1).…”

Section: Correctness Analysis (Scanline Vs Grid)supporting

confidence: 76%

Section: Introductionmentioning

confidence: 99%

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Efficient Shadows for Sampled Environment Maps

Ben-Artzi

Ramamoorthi

Agrawala

2006

Journal of Graphics Tools

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“…This becomes necessary due to the limited depth precision and a different discretization when rasterizing from the eye and the light. Layered attenuation maps compute an approximate shadow by combining several shadow maps [ARHM00]. Imagebased raytracing traces shadow rays through a set of depth images produced from a discrete set of sample points over the light source [ARHM00] or multilayer depth images including transparencies [XTP07].…”

Section: Previous Workmentioning

confidence: 99%

Sample Based Visibility for Soft Shadows using Alias‐free Shadow Maps

Sintorn

Eisemann

Assarsson

2008

Computer Graphics Forum

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This paper introduces an accurate real-time soft shadow algorithm that uses sample based visibility. Initially, we present a GPU-based alias-free hard shadow map algorithm that typically requires only a single render pass from the light, in contrast to using depth peeling and one pass per layer. For closed objects, we also suppress the need for a bias. The method is extended to soft shadow sampling for an arbitrarily shaped area-/volumetric light source using 128-1024 light samples per screen pixel. The alias-free shadow map guarantees that the visibility is accurately sampled per screen-space pixel, even for arbitrarily shaped (e.g. non-planar) surfaces or solid objects. Another contribution is a smooth coherent shading model to avoid common light leakage near shadow borders due to normal interpolation.

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“…These samples are then combined into either a Radiance Texture( [14]) or a Layered Depth Map( [1]). To reduce the number of samples needed, other methods render shadow maps for only the vertices of a linear ( [16]) or polygonal ( [25]) light source and interpolate these for each receiving pixel.…”

Section: Image Based Methodsmentioning

confidence: 99%