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Human Attention: The possibility of measuring human attention using OpenCV and the Viola-Jones face detection algorithm
KTH, School of Computer Science and Communication (CSC).
KTH, School of Computer Science and Communication (CSC).
2015 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

The question of whether an audience is focused and attentive can be of great importance. Research shows that a main concern during lectures is the varying level of attention from the students. Getting real time feedback on the students attention could give the lecturer an insight into what can be improved in terms of the material being presented. One potential way to get this feedback is to have a face detection algorithm to measure when someone is paying attention. The objective of the study is to investigate if it is possible to measure a person’s attention in a controlled environment using the OpenCV programming library and the Viola-Jones algorithm. In order to measure if someone was paying attention, a definition of attention was required. It is obvious to humans when someone is paying attention. However, this is not the case for a computer. A data set consisting of pictures of attentive and inattentive subjects was used to evaluate whether the software could be used to measure attention. The results of the study showed that OpenCV had an almost perfect detection rate with few false positives. The conclusion is therefore that the OpenCV programming library could be used to measure attention in a controlled environment. However, due to the limited scope of the study, further investigations are required in order to use it in a real-world application.

Place, publisher, year, edition, pages
2015.
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-166584OAI: oai:DiVA.org:kth-166584DiVA: diva2:811405
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Available from: 2015-05-28 Created: 2015-05-12 Last updated: 2015-05-28Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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More styles
Language
  • de-DE
  • en-GB
  • en-US
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Output format
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