Robust adaptive sampling for Monte-Carlo-based rendering

Anthony Pajot , Loïc Barthe (1, 2) , Mathias Paulin (1, 2)

1 IRIT-VORTEX - Visual Objects from Reality To Expression
2 UT3 - Université Toulouse III - Paul Sabatier

Computation times of Monte-Carlo-based rendering methods can be lowered by correctly focusing processing power on the parts of the image where convergence is harder to reach. This can be done efficiently by estimating each pixel's error, or better, using a measure of quality of the pixel (such as entropy-based methods). However, since these last methods do not uniformize the error over the pixels, they are not very well suited for progressive or time-constrained computations.

Mots clés: Monte-Carlo; adaptive sampling; rendering

Domaines: Synthèse d'image et réalité virtuelle [cs.GR]

Anthony Pajot, Loïc Barthe, Mathias Paulin. Robust adaptive sampling for Monte-Carlo-based rendering. SIGGRAPH Asia 2011, Dec 2011, Hong Kong, China. Association for Computing Machinery, New York, SA '11: SIGGRAPH Asia 2011 Posters, article 49, pp.49:1, 2011, SIGGRAPH Asia 2011 Posters. ⟨10.1145/2073304.2073359⟩. ⟨hal-01518537⟩