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Realtime Mosaicing of Video Stream from µUAV
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
2012 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Realtidsmosaik av video från µUAV (Swedish)
Abstract [en]

This is a master thesis of the Master of Science degree program in Applied Physics and Electrical Engineering (Y) at Linköping University. The goal of the projectis to develop an application for creating a map in real time from a video camera on a miniature unmanned aerial vehicle. This thesis project and report is a first exploratory study for this application. It implements a prototype method and evaluates it on sample sequences from an on-board video camera. The method first looks for good points to follow in the image and then tracks them in a sequence.The image is then pasted, or merged, together with previous images so that points from the different images align.

Two methods to find good points to follow are examined with focus on real-time performance. The result is that the much faster FAST detector method yielded satisfactory results good enough to replace the slower standard method of the Harris-Stephens corner detector.

It is also examined whether it is possible to assume that the ground is a flat surface in this application or if a computationally more expensive method estimating altitude information has to be used. The result is that at high altitudes or when the ground is close to flat in reality and the camera points straight downwards a two-dimensional method will do. If flying lower or with high objects in the picture, which is often the case in this application, it must to be taken into account that the points really are at different heights, hence the ground can not be assumed to be flat.

Place, publisher, year, edition, pages
2012. , p. 65
Keywords [en]
Image Mosaicing, μUAV, Aerial Imagery, Automated Cartography
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:liu:diva-76357ISRN: LiTH-ISY-EX--07/4140--SEOAI: oai:DiVA.org:liu-76357DiVA, id: diva2:514063
External cooperation
Instrument Control Sweden AB
Subject / course
Computer Vision Laboratory
Presentation
2012-03-22, Signalen, Linköpings Universitet, B-huset, Linköping, 13:15 (Swedish)
Uppsok
Technology
Supervisors
Examiners
Available from: 2012-05-25 Created: 2012-04-04 Last updated: 2012-05-25Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • 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