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Speed-invariant video comparison for robust human action recognition
Linnaeus University, Faculty of Technology, Department of Computer Science.
2017 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

As cameras and especially 3D cameras got affordable within recent years they can be used by a wider range of people. Human action recognition based on 3D coordinates recorded with such devices including a depth camera made it possible to compute video data easier. Many already published papers ignore the difference of speed within the execution of the same action. This paper suggests and evaluates multiple algorithms handling that problem based on Dynamic Time Warping and compares them with regard to runtime and accuracy. An additional algorithm from Softwerk AB is analyzed, adjusted and compared. An approach for a fast and robust algorithm able to compute a massive amount of stored sequences is proposed within this paper. The new algorithm depends on further research as not all prerequisites are met yet.

Place, publisher, year, edition, pages
2017. , p. 17
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:lnu:diva-60293OAI: oai:DiVA.org:lnu-60293DiVA, id: diva2:1069346
External cooperation
Softwerk AB
Subject / course
Computer Science
Presentation
2017-01-26, 14:20 (English)
Supervisors
Examiners
Available from: 2017-01-30 Created: 2017-01-30 Last updated: 2018-01-13Bibliographically approved

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fulltext(910 kB)135 downloads
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Type fulltextMimetype application/pdf

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
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