Reinforcement learning for light transport

US10115229B2 · kind B2 · utility

Assignee

• NVIDIA Corporation · US

Inventors

• Ken Patrik Dahm · Berlin, DE
• Alexander Keller · Berlin, DE

Key dates

• Filing date: Jul 12, 2017
• Grant date: Oct 30, 2018
• Expiry date: Jul 12, 2037

Classification

• Technology area (CPC G): Physics
• CPC primary: G06T15/80
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

A method for light transport includes steps of initializing a data structure that is configured to provide an importance value for each incident sample in a three-dimensional (3D) scene and tracing, in a direction from an origin, a ray of a plurality of rays through the 3D scene to intersect an object at a hitpoint. Additional steps include selecting a next direction of the ray according to a distribution of the importance values at the hitpoint, tracing the ray in the next direction to find a next hitpoint, updating a first importance value corresponding to the hitpoint using a second importance value corresponding to the next hitpoint, and setting the hitpoint of the ray to the next hitpoint. The additional steps are repeated until the next hitpoint is an endpoint. A contribution, based on each hitpoint and the endpoint, to a pixel that is intersected by the ray is recorded.