Per-Vertex Defocus Blur for Stochastic Rasterization
By Jacob Munkberg1, Robert Toth1, Tomas Akenine-Möller1,2
1Intel Corporation, 2Lund University
We present user-controllable and plausible defocus blur for a stochastic rasterizer. We modify circle of confusion coefficients per vertex to express more general defocus blur, and show how the method can be applied to limit the foreground blur, extend the in-focus range, simulate tilt-shift photography, and specify per-object defocus blur. Furthermore, with two simplifying assumptions, we show that existing triangle coverage tests and tile culling tests can be used with very modest modifications. Our solution is temporally stable and handles simultaneous motion blur and depth of field.
Read the preprint paper: Per-Vertex Defocus Blur for Stochastic Rasterization [PDF 8.4 MB], Video [MP4 48.2 MB],
Presented at Eurographics Symposium of Rendering 2012
Per-Vertex Defocus Blur for Stochastic Rasterization. Jacob Munkberg, Robert Toth, Tomas Akenine-Möller. In Computer Graphics Forum, Volume 31, Number 4, Eurographics Symposium of Rendering 2012, pp. 1385-1389.
The definitive version is available at http://diglib.eg.org/