Work

A Data-Driven Paradigm for Precomputed Radiance Transfer

Year: 2022

Type: article

Abstract: In this work, we explore a change of paradigm to build Precomputed Radiance Transfer (PRT) methods in a data-driven way. This paradigm shift allows us to alleviate the difficulties of building traditional PRT methods such as defining a reconstruction basis, coding a dedicated path tracer to compute a transfer function, etc. Our objective is to pave the way for Machine Learned methods by providing a simple baseline algorithm. More specifically, we demonstrate real-time rendering of indirect illumination in hair and surfaces from a few measurements of direct lighting. We build our baseline from pairs of direct and indirect illumination renderings using only standard tools such as Singular Value Decomposition (SVD) to extract both the reconstruction basis and transfer function.

Source: Proceedings of the ACM on Computer Graphics and Interactive Techniques

DOI: 10.1145/3543864

Authors: Laurent Belcour, Thomas Deliot, Wilhem Barbier, Cyril Soler

Institution: Institut national de recherche en sciences et technologies du numérique

Language: English

Topic: Computer Graphics and Visualization Techniques

Subfield: Computer Graphics and Computer-Aided Design

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

Funder: Agence Nationale de la Recherche

Award: Comprehensive Analysis of Light Transport Operators for image synthesis.