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5D Covariance Tracing for Efficient Defocus and Motion Blur

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dc.contributor Fredo Durand en_US
dc.contributor.advisor Fredo Durand Belcour, Laurent en_US Soler, Cyril en_US Subr, Kartic en_US Holzschuch, Nicolas en_US Durand, Fredo en_US
dc.contributor.other Computer Graphics en 2012-11-16T18:00:09Z 2012-11-16T18:00:09Z 2012-11-16
dc.description.abstract The rendering of effects such as motion blur and depth-of-field requires costly 5D integrals. We dramatically accelerate their computation through adaptive sampling and reconstruction based on the prediction of the anisotropy and bandwidth of the integrand. For this, we develop a new frequency analysis of the 5D temporal light-field, and show that first-order motion can be handled through simple changes of coordinates in 5D. We further introduce a compact representation of the spectrum using the co- variance matrix and Gaussian approximations. We derive update equations for the 5 × 5 covariance matrices for each atomic light transport event, such as transport, occlusion, BRDF, texture, lens, and motion. The focus on atomic operations makes our work general, and removes the need for special-case formulas. We present a new rendering algorithm that computes 5D covariance matrices on the image plane by tracing paths through the scene, focusing on the single-bounce case. This allows us to reduce sampling rates when appropriate and perform reconstruction of images with complex depth-of-field and motion blur effects. en_US
dc.format.extent 19 p. en_US
dc.relation.ispartofseries MIT-CSAIL-TR-2012-034
dc.subject Rendering en_US
dc.subject Computer Graphics en_US
dc.subject Fourier en_US
dc.title 5D Covariance Tracing for Efficient Defocus and Motion Blur en_US

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