Visually Comparing Rendering Performance from Multiple Perspectives
Faculty/Professorship: | Information Visualisation |
Author(s): | Tarner, Hagen; Bruder, Valentin; Frey, Steffen; Ertl, Thomas; Beck, Fabian ![]() |
Title of the compilation: | Vision, Modeling, and Visualization |
Editors: | Bender, Jan; Botsch, Mario; Keim, Daniel A. |
Conference: | VMV 2022 |
Publisher Information: | Eindhoven : The Eurographics Association |
Year of publication: | 2022 |
Pages: | 115-125 |
ISBN: | 978-3-03868-189-2 |
Language(s): | English |
DOI: | 10.2312/VMV.20221211 |
Abstract: | Evaluation of rendering performance is crucial when selecting or developing algorithms, but challenging as performance can largely differ across a set of selected scenarios. Despite this, performance metrics are often reported and compared in a highly aggregated way. In this paper we suggest a more fine-grained approach for the evaluation of rendering performance, taking into account multiple perspectives on the scenario: camera position and orientation along different paths, rendering algorithms, image resolution, and hardware. The approach comprises a visual analysis system that shows and contrasts the data from these perspectives. The users can explore combinations of perspectives and gain insight into the performance characteristics of several rendering algorithms. A stylized representation of the camera path provides a base layout for arranging the multivariate performance data as radar charts, each comparing the same set of rendering algorithms while linking the performance data with the rendered images. To showcase our approach, we analyze two types of scientific visualization benchmarks. |
GND Keywords: | Rendering; Leistungsbewertung; Algorithmentheorie; Vision, Modeling and Visualization |
Keywords: | performance visualization, visual comparison |
DDC Classification: | 004 Computer science |
RVK Classification: | ST 320 |
Peer Reviewed: | Ja |
International Distribution: | Ja |
Open Access Journal: | Ja |
Type: | Conferenceobject |
URI: | https://fis.uni-bamberg.de/handle/uniba/57258 |
Release Date: | 14. December 2022 |

originated at the
University of Bamberg
University of Bamberg