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High-quality Monte Carlo image synthesis requires the ability to importance sample realistic BRDF models. However, analytic sampling algorithms exist only for the Phong model and its derivatives such as Lafortune and Blinn-Phong. This paper demonstrates ...

2016726 — An image sensor is a device that allows the camera to convert photons – that is, light – into electrical signals that can be interpreted by the ...

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Stochastic or distribution ray tracing is a display technique that can generate photorealistic images. As with standard ray tracing, the amount of light received by a point in a scene is calculated by sampling the incoming light by sending shadow rays from that point to all light sources in the scene. For area light sources, a number of rays are sent. Rays not blocked by other objects in the scene contribute to the illumination of a point. In distribution ray tracing, the shadow ray direction is chosen in a random manner within the sampling domain to avoid the aliasing that would occur with regular and deterministic sampling. However, stochastic sampling itself leads to small variations in the amount of light, which will show up as noise in the image. This variance can be reduced with importance sampling, which directs the main sampling effort to those areas that are expected to give the most significant contribution. Such a sampling distribution can be derived either a priori by analyzing the scene or dynamically during the sampling process. This paper describes the above-mentioned Monte Carlo techniques for sampling area light sources that are approximated by spheres, cylinders, polygons, and triangles. Formulas for probability density functions are derived for both standard sampling and low-variance importance sampling. Furthermore, the authors present a method to choose one or a few light sources from a large number of light sources on the basis of their estimated proportional contribution. This method is useful when many samples are taken for each pixel. It makes ray tracing feasible for scenes with many light sources. Most of the work reported in this paper was done by Shirley and his students in the early 1990s, and it has taken some time to appear in print (not unusual for this journal). Over the last few years, several other publications and books have appeared on this topic. These other resources are referenced in this paper. The paper, therefore, not only gives a good introduction to the basic techniques, but also provides valuable pointers to the more recent developments.

Simulating a complex luminaire such as a chandelier is expensive and slow, even using state-of-the-art algorithms. A more practical alternative is to use precomputation to accelerate rendering. Prior approaches cached information on an aperture surface ...

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High-quality Monte Carlo image synthesis requires the ability to importance sample realistic BRDF models. However, analytic sampling algorithms exist only for the Phong model and its derivatives such as Lafortune and Blinn-Phong. This paper demonstrates ...

The problem treated is the efficient use of Monte Carlo methods for integrals over spherical or plane domains, depending on the geometry of the subject and the geometry of the space between the viewer and the subject. The authors seek an interpretation of the integral in question as a probability integral that will yield the lowest variance for a given computational effort. Since the approximation of the integral by averages (the central limit theorem) is slow (of order n -1/2 ), the choice of an appropriate probability distribution is essential. The authors discuss the theoretical arguments for the choice of such distributions and present three such distributions for integrals over spherical caps and several for plane domains of standard shapes. They also treat the practical problems arising in spatial subdivision methods, and show that their organization of subdivision based on octrees works on samples with many and with few light sources. An appendix shows that, for functions whose average of squared samples is constant, the choice of w y as the distribution function for the Monte Carlo evaluation of w y f y d m y is indeed optimal. The paper contains a useful bibliography.

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This chase controller provides instant sound-to-light chasing for a sound active light show. This device also allows for control of chase patterns by use of ...