Rendering

We present a new method for creating and enhancing the stereoscopic 3D (S3D) sensation without using the parallax disparity between an image pair.

We propose a general decomposition framework, where the final pixel color is separated into components corresponding to disjoint subsets of the space of light paths.

In this paper, we survey recent advances in this area. We distinguish between “a priori” methods that analyze the light transport equations and derive sampling rates and reconstruction filters from this analysis, and “a posteriori” methods that apply statistical techniques to sets of samples to drive the adaptive sampling and reconstruction process.

We analyze the behavior of the iteration and describe two alternative algorithms designed to suit different performance requirements

Our aim is to shed light on the subjective preferences and practical perceptual limits of stereo vision with respect to cardboarding.

Diffusion curves allow creating complex, smoothly shaded images by diffusing colors defined at curves. These methods typically require the solution of a global optimization problem (over either the pixel grid or an intermediate tessellated representation) to produce the final image, making fully parallel implementation challenging.

Efficiently computing light transport in participating media in a manner that is robust to variations in media density, scattering albedo, and anisotropy is a difficult and important problem in realistic image synthesis.

We present progressive photon beams, a new algorithm for rendering complex lighting in participating media.

We present several techniques to alleviate this limitation, allowing the light transport from clutter in a scene to be accounted for.

Modular Radiance Transfer (MRT) models coarse-scale, distant indirect lighting effects in scene geometry that scales from high-end GPUs to low-end mobile platforms. MRT eliminates scene dependent precomputation by storing compact transport on simple shapes, akin to bounce cards used in film production.