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Analysis and measurement of visuospatial complexity
Örebro University, School of Science and Technology.
2023 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

The thesis performs an analysis on visuospatial complexity of dynamic scenes, and morespecifically driving scenes in the propose of gaining a knowledge on human visual perception of the visual information present in a typical driving scene. The analysis and measurement of visual complexity is performed by utilizing two different measure modelsfor measuring visual clutter, Feature congestion clutter measure [1] and Subband entropyclutter measure[1] introduced by Rosenholtz, a cognitive science and research. The thesisrepresent the performance of the computational models on a data set consisting of sixepisodes that simulate driving scenes with different settings and combination of visualfeatures. The results of evaluating the measure models are used to introduce a formulafor measuring visual complexity of annotated images by extracting valuable informationfrom the annotated data set using Scalabel[2], an annotation web- based open source tool. 

Place, publisher, year, edition, pages
2023. , p. 26
Keywords [en]
Computer Science, Artificial Intelligence, Visuospatial Complexity, Feature Congestion, Subband Entropy, Visual Clutter, Image annotation.
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:oru:diva-106768OAI: oai:DiVA.org:oru-106768DiVA, id: diva2:1778711
Subject / course
Computer Engineering
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Examiners
Available from: 2023-07-03 Created: 2023-07-03 Last updated: 2023-07-03Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • Other style
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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