Abstract We present a method for uniformly sampling points inside the projection of a spherical cap onto a plane through the sphere's center. To achieve this, we devise two novel area‐preserving mappings from the unit square to this projection, which is often an ellipse but generally has a more complex shape. Our maps allow for low‐variance rendering of direct illumination from finite and infinite (e.g. sun‐like) spherical light sources by sampling their projected solid angle in a stratified manner. We discuss the practical implementation of our maps and show significant quality improvement over traditional uniform spherical cap sampling in a production renderer.

Abstract We present new methods for uniformly sampling the solid angle subtended by a disk. To achieve this, we devise two novel area‐preserving mappings from the unit square [0,1]2 to a spherical ellipse (i.e. the projection of the disk onto the unit sphere). These mappings allow for low‐variance stratified sampling of direct illumination from disk‐shaped light sources. We discuss how to efficiently incorporate our methods into a production renderer and demonstrate the quality of our maps, showing significantly lower variance than previous work.

This paper presents an analysis of the overestimation bias in common used filtering kernels in the context of photon mapping density estimation. We use the joint distribution of order statistics to calculate the expected value of the estimators of irradiance, and show that the estimator provided by the cone filter is not consistent unless the slope is one (yielding the triangular kernel), and that the Epanechnikov and Silverman kernels are consistent. The Gaussian filter has two different estimation biases: the original normalization constant α underestimates radiance by 46.9 percent, and the use of the kth nearest photon reduces this underestimation slightly. We also show that a new normalization constant for the Gaussian filter together with discarding the contribution of the kth nearest photon in the Gaussian and cone filter estimators produces new, consistent estimators. The specialized differential filter also benefits from the new estimate.

Abstract We present an area‐preserving parametrization for spherical rectangles which is an analytical function with domain in the unit rectangle [0, 1]2 and range in a region included in the unit‐radius sphere. The parametrization preserves areas up to a constant factor and is thus very useful in the context of rendering as it allows to map random sample point sets in [0, 1]2 onto the spherical rectangle. This allows for easily incorporating stratified, quasi‐Monte Carlo or other sampling strategies in algorithms that compute scattering from planar rectangular emitters.

Abstract This paper presents an analysis of the irradiance estimator often used in photon mapping algorithms and concludes that the classical approach with a constant kernel overestimates the correct value. We propose a new estimator that solves this problem and provide both theoretical and empirical studies to verify it.

This paper describes an approach to obtain interactive recalculation of global illumination for scenes with small moving objects (with respect to the complete geometry), on a standard PC, using density estimation techniques

We introduce an algorithm for sample positioning in a planar triangle, which can be used to make numerical integration of an arbitrary function defined on it. This algorithm has some interesting properties which make it suitable for applications in the context of realistic rendering. We use an adaptive triangle partitioning procedure, driven by an appropriate measure of the error. The underlying variance is shown to be bounded, and in fact it can be controlled, so that it approaches the minimum possible value. We show results obtained when applying the method to irradiance computation, in the context of final‐gather algorithms. We also describe a C++ class which offers all required functionality, and we made available its source code.