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Exponential Soft Shadow Mapping
Author(s) -
Shen Li,
Feng Jieqing,
Yang Baoguang
Publication year - 2013
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/cgf.12156
Subject(s) - computer science , shadow (psychology) , shadow mapping , computer vision , exponential function , function (biology) , grid , algorithm , computer graphics (images) , image (mathematics) , artificial intelligence , mathematics , psychology , mathematical analysis , geometry , evolutionary biology , psychotherapist , biology
In this paper we present an image‐based algorithm to render visually plausible anti‐aliased soft shadows in real time. Our technique employs a new shadow pre‐filtering method based on an extended exponential shadow mapping theory. The algorithm achieves faithful contact shadows by adopting an optimal approximation to exponential shadow reconstruction function. Benefiting from a novel overflow free summed area table tile grid data structure, numerical stability is guaranteed and error filtering response is avoided. By integrating an adaptive anisotropic filtering method, the proposed algorithm can produce high quality smooth shadows both in large penumbra areas and in high frequency sharp transitions, meanwhile guarantee cheap memory consumption and high performance.