Towards More Robust and Efficient Monte Carlo Methods for Realistic Image Synthesis

Abstract (2018)

Authors

Jerry Jinfeng Guo Computer Graphics and Visualisation -

Research Group

Computer Graphics and Visualisation () (TU Delft)

Realistic rendering Monte carlo methods

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http://resolver.tudelft.nl/uuid:ecaed021-2ccd-461f-b071-6d18a99b1093

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Published Date

2018

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Intelligent Systems

Research Group

Computer Graphics and Visualisation

Abstract

In this extended abstract we present our research statement, motivation and methodology for this PhD project. This PhD research focuses on Monte Carlo methods in the field of realistic image synthesis. According to various studies, widely adopted sampling schemes prove not optimal. The overall goal of this PhD research project is to improve existing Monte Carlo methods and make them more robust and efficient. We will analyze pitfalls of existing methods and propose improved mathematical models and methods accordingly. We will verify and implement our proposed models. Performance will be analyzed following rigorous design science guidelines.