5 research outputs found
Progressive Transient Photon Beams
In this work we introduce a novel algorithm for transient rendering in
participating media. Our method is consistent, robust, and is able to generate
animations of time-resolved light transport featuring complex caustic light
paths in media. We base our method on the observation that the spatial
continuity provides an increased coverage of the temporal domain, and
generalize photon beams to transient-state. We extend the beam steady-state
radiance estimates to include the temporal domain. Then, we develop a
progressive version of spatio-temporal density estimations, that converges to
the correct solution with finite memory requirements by iteratively averaging
several realizations of independent renders with a progressively reduced kernel
bandwidth. We derive the optimal convergence rates accounting for space and
time kernels, and demonstrate our method against previous consistent transient
rendering methods for participating media
Reversible Jump Metropolis Light Transport using Inverse Mappings
We study Markov Chain Monte Carlo (MCMC) methods operating in primary sample
space and their interactions with multiple sampling techniques. We observe that
incorporating the sampling technique into the state of the Markov Chain, as
done in Multiplexed Metropolis Light Transport (MMLT), impedes the ability of
the chain to properly explore the path space, as transitions between sampling
techniques lead to disruptive alterations of path samples. To address this
issue, we reformulate Multiplexed MLT in the Reversible Jump MCMC framework
(RJMCMC) and introduce inverse sampling techniques that turn light paths into
the random numbers that would produce them. This allows us to formulate a novel
perturbation that can locally transition between sampling techniques without
changing the geometry of the path, and we derive the correct acceptance
probability using RJMCMC. We investigate how to generalize this concept to
non-invertible sampling techniques commonly found in practice, and introduce
probabilistic inverses that extend our perturbation to cover most sampling
methods found in light transport simulations. Our theory reconciles the
inverses with RJMCMC yielding an unbiased algorithm, which we call Reversible
Jump MLT (RJMLT). We verify the correctness of our implementation in canonical
and practical scenarios and demonstrate improved temporal coherence, decrease
in structured artifacts, and faster convergence on a wide variety of scenes
Progressive Transient Photon Beams
In this work, we introduce a novel algorithm for transient rendering in participating media. Our method is consistent, robust and is able to generate animations of time-resolved light transport featuring complex caustic light paths in media. We base our method on the observation that the spatial continuity provides an increased coverage of the temporal domain, and generalize photon beams to transient-state. We extend stead-state photon beam radiance estimates to include the temporal domain. Then, we develop a progressive variant of our approach which provably converges to the correct solution using finite memory by averaging independent realizations of the estimates with progressively reduced kernel bandwidths. We derive the optimal convergence rates accounting for space and time kernels, and demonstrate our method against previous consistent transient rendering methods for participating media
Efficient Caustic Rendering with Lightweight Photon Mapping
Robust and efficient rendering of complex lighting effects, such as caustics, remains a challenging task. While algorithms like vertex connection and merging can render such effects robustly, their significant overhead over a simple path tracer is not always justified and â as we show in this paper â also not necessary. In current rendering solutions, caustics often require the user to enable a specialized algorithm, usually a photon mapper, and handâtune its parameters. But even with carefully chosen parameters, photon mapping may still trace many photons that the path tracer could sample well enough, or, even worse, that are not visible at all.
Our goal is robust, yet lightweight, caustics rendering. To that end, we propose a technique to identify and focus computation on the photon paths that offer significant variance reduction over samples from a path tracer. We apply this technique in a rendering solution combining path tracing and photon mapping. The photon emission is automatically guided towards regions where the photons are useful, i.e., provide substantial variance reduction for the currently rendered image. Our method achieves better photon densities with fewer light paths (and thus photons) than emission guiding approaches based on visual importance. In addition, we automatically determine an appropriate number of photons for a given scene, and the algorithm gracefully degenerates to pure path tracing for scenes that do not benefit from photon mapping
A Spatial Target Function for Metropolis Photon Tracing
International audienceThe human visual system is sensitive to relative differences in luminance, but light transport simulation algorithms based on Metropolis sampling often result in a highly nonuniform relative error distribution over the rendered image. Although this issue has previously been addressed in the context of the Metropolis light transport algorithm, our work focuses on Metropolis photon tracing. We present a new target function (TF) for Metropolis photon tracing that ensures good stratification of photons leading to pixel estimates with equalized relative error. We develop a hierarchical scheme for progressive construction of the TF from paths sampled during rendering. In addition to the approach taken in previous work, where the TF is defined in the image plane, ours can be associated with compact spatial regions. This allows us to take advantage of illumination coherence to more robustly estimate the TF while adapting to geometry discontinuities. To sample from this TF, we design a new replica exchange Metropolis scheme. We apply our algorithm in progressive photon mapping and show that it often outperforms alternative approaches in terms of image quality by a large margin