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Real-time Raytracing and Screen-space Ambient Occlusion
KTH, School of Electrical Engineering and Computer Science (EECS).
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

This paper investigates the advances in real-time ambient occlusion (AO). Topics discussed are state-of-the-art screen-space techniques and raytraced ambient occlusion. Methods compared are our screen-space ambient occlusion (SSAO) variant, horizon-based ambient occlusion(HBAO),

Unity’s scalable AO (AlchemyAO), multi-scale volumetric AO (MSVO), and raytraced AO (RTAO). The methods were compared based on the errors produced in dynamic scenes, performance and similarity to reference scenes rendered by an offline raytracer. Important dynamic scene errors were highlighted, visual results were objectively evaluated using Structural Similarity Index (SSIM) and Unity engine was used as a common platform for all the methods in order to obtain performance metrics. RTAO managed to achieve a strikingly high SSIM score, while, MSVO traded some accuracy to be the fastest of all the methods. Further analysis of different implementations and their strengths and weaknesses are provided.

Abstract [sv]

Denna studie utforskar framsteg inom realtid ambient occlusion (AO). Ämnen som diskuteras är senaste typen av screen-spaceteknik och raytraced ambient occlusion. Metoderna som jämförs är vår egen screen-space ambient occlusion (SSAO) variant, horizon-based ambient occlusion (HBAO), Unitys scalable AO (Alchemy AO), multi-scale volumetric AO (MSVO), och raytraced AO (RTAO). De olika metoderna jämfördes baserat på prestanda, likheter till referens scener och fel som tillverkas inom dynamiska scener. Viktiga dynamiska scener var markerad och de visuella resultaten var objektivt evaluerad genom användning av Structural Similarity Index (SSIM). Unity motorn användes som en gemensam plattform för alla typer av metoder för att få fram prestanda mått.

RTAO lyckades att uppnå ett högt SSIM betyg medan MSVO blev den snabbaste av alla metoder dock har lägre precision. Ytterligare analys av olika genomföringar och deras styrkor samt svagheter ingår i rapporten.

Place, publisher, year, edition, pages
2019. , p. 63
Series
TRITA-EECS-EX ; 2019:442
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-254990OAI: oai:DiVA.org:kth-254990DiVA, id: diva2:1337203
Supervisors
Examiners
Available from: 2019-07-12 Created: 2019-07-12 Last updated: 2019-07-12Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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Output format
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