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Smooth shadow boundaries with exponentially warped Gaussian filtering

Shadow mapping is widely used in computer graphics for efficiently rendering shadows in real-time applications. Shadow maps cannot be filtered as regular textures, thus their limited resolution can cause severe shadow map discretization artifacts in the rendered images. To solve this problem, several techniques have been proposed, including variance shadow maps (VSM) and exponential shadow maps (ESM). However, these techniques introduce different kinds of light leaking artifacts, which are clearly visible in moderately complex scenes. In this paper we propose a new statistical filtering method that approximates the cumulative distribution function (CDF) of depth values by a Gaussian CDF instead of bounding it with Chebyshev Inequality. This approximation significantly reduces light leaks and has similar performance and storage requirements compared to the original variance shadow map method. We also show that the combination of this technique with an exponential warp allows us to further reduce the remaining shadowing artifacts from the rendered image

This work has been supported by the Spanish Ministry of Education and Science (TIN2010-21089-C03-01, TIN2010-21089-C03-03, TIN2009-14103-C03-01), Caja Castellem-Bancaja Foundation (P1.1B2010-08, P1.1B2009-34), the European Union (Ref. 226487), Generalitat Valenciana (Project PROMETEO/2010/028), BEST/2011/287, Generalitat of Catalunya (Catalan Government) (2009-SGR-643), and TAMOP - 4.2.2.B-10/1-2010-0009

Elsevier

Manager: Ministerio de Ciencia e Innovación (Espanya)
Generalitat de Catalunya. Agència de Gestió d’Ajuts Universitaris i de Recerca
Author: Gumbau, Jesús
Sbert, Mateu
Szirmay-Kalos, László
Chover, Miguel
González, Carlos
Abstract: Shadow mapping is widely used in computer graphics for efficiently rendering shadows in real-time applications. Shadow maps cannot be filtered as regular textures, thus their limited resolution can cause severe shadow map discretization artifacts in the rendered images. To solve this problem, several techniques have been proposed, including variance shadow maps (VSM) and exponential shadow maps (ESM). However, these techniques introduce different kinds of light leaking artifacts, which are clearly visible in moderately complex scenes. In this paper we propose a new statistical filtering method that approximates the cumulative distribution function (CDF) of depth values by a Gaussian CDF instead of bounding it with Chebyshev Inequality. This approximation significantly reduces light leaks and has similar performance and storage requirements compared to the original variance shadow map method. We also show that the combination of this technique with an exponential warp allows us to further reduce the remaining shadowing artifacts from the rendered image
This work has been supported by the Spanish Ministry of Education and Science (TIN2010-21089-C03-01, TIN2010-21089-C03-03, TIN2009-14103-C03-01), Caja Castellem-Bancaja Foundation (P1.1B2010-08, P1.1B2009-34), the European Union (Ref. 226487), Generalitat Valenciana (Project PROMETEO/2010/028), BEST/2011/287, Generalitat of Catalunya (Catalan Government) (2009-SGR-643), and TAMOP - 4.2.2.B-10/1-2010-0009
Document access: http://hdl.handle.net/2072/296933
Language: eng
Publisher: Elsevier
Rights: Tots els drets reservats
Subject: Infografia
Computer graphics
Imatges -- Processament
Image processing
Title: Smooth shadow boundaries with exponentially warped Gaussian filtering
Type: info:eu-repo/semantics/article
Repository: Recercat

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