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Continuous shading of curved surfaces

TLDR
The surface is approximated by small polygons in order to solve easily the hidden-parts problem, but the shading of each polygon is computed so that discontinuities of shade are eliminated across the surface and a smooth appearance is obtained.
Abstract
A procedure for computing shaded pictures of curved surfaces is presented. The surface is approximated by small polygons in order to solve easily the hidden-parts problem, but the shading of each polygon is computed so that discontinuities of shade are eliminated across the surface and a smooth appearance is obtained. In order to achieve speed efficiency, the technique developed by Watkins is used which makes possible a hardware implementation of this algorithm.

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Journal ArticleDOI

A progressive refinement approach to fast radiosity image generation

TL;DR: A reformulated radiosity algorithm is presented that produces initial images in time linear to the number of patches, which brings the use of radiosity for interactive rendering within reach and has implications for the use and development of current and future graphics workstations.
Proceedings ArticleDOI

The haptic display of complex graphical environments

TL;DR: This work has developed a haptic rendering system that allows for the efficient tactile display of graphical information and uses a common high-level framework to model contact constraints, surface shading, friction and tex ture.
Book

ARTS: accelerated ray-tracing system

TL;DR: After investigating both simple spatial enumeration and a hybrid octree approach, 3DDDA is developed, a 3D line generator for efficient traversing of both structures and provides an order of magnitude improvement in processing speed compared to other known ray-tracing methods.
Journal ArticleDOI

Three-dimensional Volume Rendering of Spiral CT Data: Theory and Method

TL;DR: Three-dimensional volume rendering is useful in a wide variety of applications but is just now being incorporated into commercially available software packages for medical imaging, with wider availability and improved cost-to-performance ratios in computing.
Posted Content

Accelerating 3D Deep Learning with PyTorch3D

TL;DR: 1. Accelerating 3D Deep Learning with PyTorch3D, arXiv 2007 2. Mesh R-CNN, ICCV 2019 3. SynSin: End-to-end View Synthesis from a Single Image, CVPR 2020 4. Fast Differentiable Raycasting for Neural Rendering using Sphere-based Representations.