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User perception of varying level of detail for Imposters
KTH, School of Electrical Engineering and Computer Science (EECS).
KTH, School of Electrical Engineering and Computer Science (EECS).
2019 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
Användaruppfattning av varierad detaljnivå för Imposters (Swedish)
Abstract [en]

As the time to render frames increases with the amount of 3D models present and the level of detail of these models, finding a way to render these objects more efficiently would allow real time applications to render a larger number of objects. One such technique is Imposters, but their level of detail is limited by texture memory, especially for animated objects. A user study was performed to investigate how changing the level of detail of the angles or frames for imposters in a crowd simulation impacts the perceived realism. The results of this study show that the participants’ confidence in their answers fell as the overall quality rose, but the share of answers that aligned with the higher quality side rose together with overall quality.

Abstract [sv]

Eftersom att tiden det tar att rendera bildrutor ökar med antalet 3D-modeller som avbildas och med modellernas detaljnivå skulle det tillåta realtidsapplikationer att avbilda fler objekt om ett sätt att effektivare avbilda dessa objekt hittas. En sådan teknik är Imposters, men deras detaljrikedom begränsas av texturminne, särskilt när det kommer till animerade objekt. En användarstudie utfördes för att undersöka hur förändringar i detaljnivåer med avseende på antalet vinklar och bildrutor för Imposters i en simulering av en folkmassa påverkar den upplevda realismen. Resultaten av studien pekar på att deltagarnas tilltro till sina svar minskade i takt med att kvalitén ökade, däremot ökade andelen svar där sidan med högre kvalité valdes när kvalitén överlag var högre.

Place, publisher, year, edition, pages
2019. , p. 17
Series
TRITA-EECS-EX ; 2019:548
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-263157OAI: oai:DiVA.org:kth-263157DiVA, id: diva2:1366889
Supervisors
Examiners
Available from: 2019-11-18 Created: 2019-10-31 Last updated: 2019-11-18Bibliographically approved

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Type fulltextMimetype application/pdf

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Output format
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