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Optimization Methods for Direct Volume Rendering on the Client Side Web
Linköping University, Department of Electrical Engineering, Information Coding.
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Volume visualization has been made available on the web using the Direct Volume Rendering (DVR) technique, powered by the WebGL 1 API. While the technique produces visually pleasing output, the performance of the prototypes that implement this leave much desired. 2017 saw the release of the next version of WebGL, WebGL 2.0 and the introduction of WebAsssembly. These APIs and formats are promising tools for formulating a DVR application that can do high performance rendering at interactive frame rates.

This thesis investigates, implements and evaluates a prototype application that utilizes the optimization methods of Adaptive Texture Maps, Octree Empty Space Skipping and Distance Transform Empty Space Skipping. The Distance Transform is further evaluated by a CPU bound and a GPU bound algorithm implementation. The techniques are assessed on readily available off the shelf devices and hardware. The performance of the prototype application ran on these devices is quantified by measuring computation times of costly operations, and measuring frames per second.

It is concluded that for different hardware, the methods have different properties. While higher FPS is achieved for all devices by utilizing some combination of the optimization methods, the distance transform is the most consistent. A discussion on embedded devices and their quirks is also held, where memory constraints and the resolution of the data is of greater importance than on the non-embedded devices. This results in some suggested actions that can be taken to also potentially enable high-performance rendering of higher resolution data on these devices.

Place, publisher, year, edition, pages
2019. , p. 53
Keywords [en]
Volume Visualization, Ray Casting, Optimization, GPU, Web
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:liu:diva-158134ISRN: LiTH-ISY-EX-ET--19/5204--SEOAI: oai:DiVA.org:liu-158134DiVA, id: diva2:1330460
External cooperation
AMRA Medical
Subject / course
Electrical Engineering
Presentation
2019-06-05, SYSTEMET, 10:00 (English)
Supervisors
Examiners
Available from: 2019-06-28 Created: 2019-06-25 Last updated: 2019-06-28Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf