Raytracing is a long-established means to simulate physically accurate light propagation. Increasing availability and power of highly-parallel computing, such as cloud-based clusters and dedicated graphics hardware, means that rendering algorithms can produce high resolution output very quickly. This means raytracing can now be used as a forward model in optimization algorithms to improve the performance of computational imaging systems. This thesis considers the hypothesis that this rendering-based optimization approach for computational imaging systems will gain increasingly-widespread use in the future. This thesis evaluates two distinct uses for rendering-based optimization: a near- eye display and a surface reconstruction algorithm for active 3D scanners. In the first, a novel display architecture produces spatially varying focus for the user. Rendering-based optimization corrects hardware-induced optical distortions to produce an improved retinal image. The second use case flexibly corrects for multibounce interference in active 3D scanners, including arbitrary scene reflectance, using rendering-based optimization.

Last modified

• 10/21/2019

Creator

• Nathan Seigo Matsuda

DOI

• https://doi.org/10.21985/n2-c6dg-rn73

Subject

• Computer Science

Keyword

• Computer science

Date created

• 2018-01-01

Resource type

• Dissertation

Rights statement

• In Copyright