Rendering global light transport in real-time using machine learning
US9013496B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 19, 2012 |
| Grant date | Apr 21, 2015 |
| Priority date | — |
| Expiry date | Jan 26, 2033 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T15/80
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Some implementations disclosed herein provide techniques and arrangements to render global light transport in real-time or near real-time. For example, in a pre-computation stage, a first computing device may render points of surfaces (e.g., using multiple light bounces and the like). Attributes for each of the points may be determined. A plurality of machine learning algorithms may be trained using particular attributes from the attributes. For example, a first machine learning algorithm may be trained using a first portion of the attributes and a second machine learning algorithm may be trained using a second portion of the attributes. The trained machine learning algorithms may be used by a second computing device to render components (e.g., diffuse and specular components) of indirect shading in real-time.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.