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Expected Damage of Projectile-Like Spell Effects in Games
Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.
2018 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Background. Many video games make use of particle effects to portray magic abilities known as spells. Different spells may have large variation in behaviour and colour. Aside from their different appearance, the spells often deal a different amount of damage.

Objectives. The aim of this paper is to evaluate how velocity, scale, and direction, as well as the colour orange and blue affect the expected damage of a projectile-like spell.Methods. A perceptual experiment with a 2AFC was conducted where participants compared various spells with different values of velocity, scale, direction, and colour. The participants were asked to select the spell that they expect to deal the most damage.

Results. Scale had a larger impact on the expected damage of a spell than velocity. The largest and fastest spells with an added sinus based direction in the x-axis were expected to cause the most damage. However, the difference between these spells and the largest and fastest spells without the added direction was not found to be statistically significant. The orange spells were rated as more damage causing in all cases compared to the blue spells. The difference between the blue and orange preference in two of these cases were however not large enough to be statistically significant.

Conclusions. The results showed that the visual attributes of a particle-based spell affect its perceived damage with the scale having a greater impact than velocity and orange being the colour most often associated with higher damage. The effect of an added direction could not be evaluated due the result from the direction spells not being statistically significant.

Place, publisher, year, edition, pages
2018.
Keywords [en]
Perception, Spells, Particle Systems, Games.
National Category
Other Computer and Information Science
Identifiers
URN: urn:nbn:se:bth-16672OAI: oai:DiVA.org:bth-16672DiVA, id: diva2:1229357
Educational program
UDGTA Technical artist for games
Supervisors
Examiners
Available from: 2018-07-02 Created: 2018-06-29 Last updated: 2018-07-03Bibliographically approved

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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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