Metropolis Instant Radiosity

Abstract

a) -Office (b) -Conference (c) -Cabin (d) -Theater (e) -Cruiser (f) (g) -Three Dragon Room (h) -A Jack-o-Lantern in (g) Figure 1: Some images rendered with Metropolis Instant Radiosity, a coherent ray tracer, and 1024 V PLs. Our method which consists in describing a Virtual Point Light (V PL) sampler as a Markovian process provides very satisfactory results in many cases: in mostly directly-lit scenes as shown in (a), (b) and, (c) with many light sources or complex scenes as shown in (d) and (e), and with very difficult visibility issues as shown in Figures (f), (g), and (h). AbstractWe present Metropolis Instant Radiosity (MIR), an unbiased algorithm to solve the Light Transport problem. MIR is a hybrid technique which consists in representing the incoming radiance field by a set of Virtual Point Lights (V PLs) and in computing the response of all sensors in the scene (i.e. camera captors) by accumulating their contributions. In contrast to other similar approaches, we propose to sample the V PLs with an innovative Multipletry Metropolis-Hastings (MT MH) Algorithm: the goal is to build an efficient, aggressive, and unconditionally robust variance reduction method that works well regardless of the scene layout. Finally, we present a fast ray tracing implementation using MIR and show how our complete rendering pipeline can produce high-quality and high-resolution pictures in a few seconds.

Importance Caching for Complex Illumination

“…However, obtaining such a PDF in practice is unfeasible, particularly because the visibility function V is not given in a closed form, and/or the incoming radiance may not be known. The state-of-the-art importance sampling methods build distributions that include some of the terms in f , usually the product BL, for sampling environment [CJAMJ05,CETC06,CAM08b] Importance-driven VPL generation has recently received attention [WBS03,SIMP06,SIP07,GS10]. These methods sample VPLs based on their total image contribution, but do not adapt to individual locations.…”

Autonomous Lighting Agents in Photon Mapping

“…Photon mapping presented in [4,5] is currently one of the most efficient physically based algorithm capable of global illumination rendering. Compared to other global illumination methods like radiosity [6,7] or Metropolis Light Transport [8,9], photon mapping is a robust and consistent two-pass algorithm [10], is able to handle many light effects including caustics, and is modular since it separates illumination in several layers [4]. The first pass traces photons from all lights through the scene and stores them, at hit points, in so called photon map.…”

Efficient streaming of 3D scenes with complex geometry and complex lighting

“…Stochastic solutions have also been implemented on GPUs, such as those based on Photon-Mapping [Purcell et al 2003] or radiance caching [Gautron et al 2005]. Real time is only achieved with Instant Radiosity [Keller 1997;Segovia et al 2007] combined with incremental techniques [Laine et al 2007], but its visual quality strongly depends on the geometric accuracy. In a streaming context, this is hardly achievable.…”