@inproceedings{5e80d005d1b24dab9e3c61449c7b4a0b,
title = "Cinema Darkroom: A Deferred Rendering Framework for Large-Scale 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. ",
keywords = "Deferred Rendering, Image Databases, Image-Based Shading, In Situ Visualization, Post Hoc Analysis",
author = "Jonas Lukasczyk and Christoph Garth and Matthew Larsen and Wito Engelke and Ingrid Hotz and David Rogers and James Ahrens and Ross MacIejewski",
note = "Funding Information: This work was supported by the U.S. Department of Homeland Security under Grant Award 2017-ST-061-QA0001and 17STQAC00001-03-03,and the National Science Foundation Program under Award No. 1350573. The views and conclusions contained in this document are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of the U.S. Department of Homeland Security. This work was also partially supported by the German research foundation (DFG) through the IRTG 2057, and by a grant from the Swedish Foundation for Strategic Research (SSF, BD15-0082), the SeRC (Swedish e-Science Research Center) and the ELLIIT environmentfor strategic research in Sweden. Publisher Copyright: {\textcopyright} 2020 IEEE.; 10th IEEE Symposium on Large Data Analysis and Visualization, LDAV 2020 ; Conference date: 25-10-2020",
year = "2020",
month = oct,
doi = "10.1109/LDAV51489.2020.00011",
language = "English (US)",
series = "Proceedings - 2020 IEEE 10th Symposium on Large Data Analysis and Visualization, LDAV 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "37--41",
booktitle = "Proceedings - 2020 IEEE 10th Symposium on Large Data Analysis and Visualization, LDAV 2020",
}