liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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
Robust Real-Time Estimation of Region Displacements in Video Sequences
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
2007 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The possibility to use real-time computer vision in video sequences gives many opportunities for a system to interact with the environment. Possible ways for interaction are e.g. augmented reality like in the MATRIS project where the purpose is to add new objects into the video sequence, or surveillance where the purpose is to find abnormal events.

The increase of the speed of computers the last years has simplified this process and it is now possible to use at least some of the more advanced computer vision algorithms that are available. The computational speed of computers is however still a problem, for an efficient real-time system efficient code and methods are necessary. This thesis deals with both problems, one part is about efficient implementations using single instruction multiple data (SIMD) instructions and one part is about robust tracking.

An efficient real-time system requires efficient implementations of the used computer vision methods. Efficient implementations requires knowledge about the CPU and the possibilities given. In this thesis, one method called SIMD is explained. SIMD is useful when the same operation is applied to multiple data which usually is the case in computer vision, the same operation is executed on each pixel.

Following the position of a feature or object in a video sequence is called tracking. Tracking can be used for a number of applications. The application in this thesis is to use tracking for pose estimation. One way to do tracking is to cut out a small region around the feature, creating a patch and find the position on this patch in the other frames. To find the position, a measure of the difference between the patch and the image in a given position is used. This thesis thoroughly investigates the sum of absolute difference (SAD) error measure. The investigation involves different ways to improve the robustness and to decrease the average error. One method to estimate the average error, the covariance of the position error is proposed. An estimate of the average error is needed when different measurements are combined.

Finally, a system for camera pose estimation is presented. The computer vision part of this system is based on the result in this thesis. This presentation contains also a discussion about the result of this system.

Place, publisher, year, edition, pages
2007. , 55 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1296
Keyword [en]
tracking, subpixel, real time, covariance, pose estimation
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-8006Local ID: LIU-TEK-LIC-2007:5ISBN: 978-91-85715-86-2 (print)OAI: oai:DiVA.org:liu-8006DiVA: diva2:22906
Presentation
2007-01-26, Algoritmen, Hus b, Campus Valla, Linköping, 10:15 (English)
Opponent
Supervisors
Note
Report code: LIU-TEK-LIC-2007:5. The report code in the thesis is incorrect.Available from: 2007-01-18 Created: 2007-01-18 Last updated: 2016-05-04

Open Access in DiVA

fulltext(472 kB)795 downloads
File information
File name FULLTEXT01.pdfFile size 472 kBChecksum MD5
d14c0723bbc93ff31c459bf77ce6a72fa33ab3843be754226cb038872e712d408f7fc410
Type fulltextMimetype application/pdf

Authority records BETA

Skoglund, Johan

Search in DiVA

By author/editor
Skoglund, Johan
By organisation
Computer VisionThe Institute of Technology
Computer Vision and Robotics (Autonomous Systems)

Search outside of DiVA

GoogleGoogle Scholar
Total: 795 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 727 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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