Parameter Estimation of BSSRDF for Heterogeneous Materials
نویسندگان
چکیده
Rendering of highly scattering media is computationally expensive in general. While existing BSSRDF models can accurately and efficiently approximate light scattering in homogeneous media, we still have to resort to costly Monte Carlo simulation for heterogeneous media. We propose a simple parameter estimation method which enables homogeneous BSSRDF models to approximate the appearance of heterogeneous media. The main idea is to estimate the input optical parameters of a given homogeneous BSSRDF model such that the output well approximates light transport within heterogeneous media. Our method takes spatially varying optical coefficients into account by taking averages of the coefficients around the incident and exitant points. This approach is motivated by the path integral theory which predicts how wide the beam of light will spread in heterogeneous media. Since our method provides parameters for homogeneous BSSRDF models, it is applicable to many existing BSSRDF models and easy to integrate into existing rendering systems. We show that our modification produces more accurate results than the existing heuristics with the same goal.
منابع مشابه
Distributed Incremental Least Mean-Square for Parameter Estimation using Heterogeneous Adaptive Networks in Unreliable Measurements
Adaptive networks include a set of nodes with adaptation and learning abilities for modeling various types of self-organized and complex activities encountered in the real world. This paper presents the effect of heterogeneously distributed incremental LMS algorithm with ideal links on the quality of unknown parameter estimation. In heterogeneous adaptive networks, a fraction of the nodes, defi...
متن کاملA Dual-Beam Method-of-Images 3D Searchlight BSSRDF
We present a novel BSSRDF for rendering translucent materials. Angular effects lacking in previous BSSRDF models are incorporated by using a dual-beam formulation. We employ a Placzek’s Lemma interpretation of the method of images and discard diffusion theory. Instead, we derive a plane-parallel transformation of the BSSRDF to form the associated BRDF and optimize the image confiurations such t...
متن کاملSampling BSSRDFs with non-perpendicular incidence
Sub-surface scattering is key to our perception of translucent materials. Models based on diffusion theory are used to render such materials in a realistic manner by evaluating an approximation of the material BSSRDF at any two points of the surface. Under the assumption of perpendicular incidence, this BSSRDF approximation can be tabulated over 2 dimensions to provide fast evaluation and impor...
متن کاملBayes, E-Bayes and Robust Bayes Premium Estimation and Prediction under the Squared Log Error Loss Function
In risk analysis based on Bayesian framework, premium calculation requires specification of a prior distribution for the risk parameter in the heterogeneous portfolio. When the prior knowledge is vague, the E-Bayesian and robust Bayesian analysis can be used to handle the uncertainty in specifying the prior distribution by considering a class of priors instead of a single prior. In th...
متن کاملParameter Estimation of Some Archimedean Copulas Based on Minimum Cramér-von-Mises Distance
The purpose of this paper is to introduce a new estimation method for estimating the Archimedean copula dependence parameter in the non-parametric setting. The estimation of the dependence parameter has been selected as the value that minimizes the Cramér-von-Mises distance which measures the distance between Empirical Bernstein Kendall distribution function and true Kendall distribution functi...
متن کامل