Cinema Darkroom: A Deferred Rendering Framework for Large-Scale Datasets

TL;DR

Cinema Darkroom introduces a deferred rendering framework that precomputes geometry buffers for large datasets, enabling interactive visualization adjustments without reprocessing the entire dataset.

Contribution

It proposes a novel decoupled rendering approach that separates geometry processing from shading, improving efficiency and flexibility for large-scale dataset visualization.

Findings

Efficiently handles large datasets with a single G-Buffer computation.

Enables interactive visualization parameter adjustments post hoc.

Demonstrates effectiveness on real-world datasets.

Abstract

This paper presents a framework that fully leverages the advantages of a deferred rendering approach for the interactive visualization of large-scale datasets. Geometry buffers (G-Buffers) are generated and stored in situ, and shading is performed post hoc in an interactive image-based rendering front end. This decoupled framework has two major advantages. First, the G-Buffers only need to be computed and stored once---which corresponds to the most expensive part of the rendering pipeline. Second, the stored G-Buffers can later be consumed in an image-based rendering front end that enables users to interactively adjust various visualization parameters---such as the applied color map or the strength of ambient occlusion---where suitable choices are often not known a priori. This paper demonstrates the use of Cinema Darkroom on several real-world datasets, highlighting CD's ability to effectively decouple the complexity and size of the dataset from its visualization.