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Modern Stereo Correspondence Algorithms: Investigation and Evaluation
Linköping University, Department of Electrical Engineering, Information Coding.
2010 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Many different approaches have been taken towards solving the stereo correspondence problem and great progress has been made within the field during the last decade. This is mainly thanks to newly evolved global optimization techniques and better ways to compute pixel dissimilarity between views. The most successful algorithms are based on approaches that explicitly model smoothness assumptions made about the physical world, with image segmentation and plane fitting being two frequently used techniques.

Within the project, a survey of state of the art stereo algorithms was conducted and the theory behind them is explained. Techniques found interesting were implemented for experimental trials and an algorithm aiming to achieve state of the art performance was implemented and evaluated. For several cases, state of the art performance was reached.

To keep down the computational complexity, an algorithm relying on local winner-take-all optimization, image segmentation and plane fitting was compared against minimizing a global energy function formulated on pixel level. Experiments show that the local approach in several cases can match the global approach, but that problems sometimes arise – especially when large areas that lack texture are present. Such problematic areas are better handled by the explicit modeling of smoothness in global energy minimization.

Lastly, disparity estimation for image sequences was explored and some ideas on how to use temporal information were implemented and tried. The ideas mainly relied on motion detection to determine parts that are static in a sequence of frames. Stereo correspondence for sequences is a rather new research field, and there is still a lot of work to be made.

Place, publisher, year, edition, pages
2010. , 102 p.
Keyword [en]
stereo correspondence, stereo matching, cost function, cost aggregation, image segmentation, plane fitting, RANSAC, graph cuts, belief propagation, disparity, depth estimation
National Category
Computer Vision and Robotics (Autonomous Systems) Other Engineering and Technologies not elsewhere specified Computational Mathematics
Identifiers
URN: urn:nbn:se:liu:diva-57853ISRN: LiTH-ISY-Ex--10/4432--SEOAI: oai:DiVA.org:liu-57853DiVA: diva2:328101
Presentation
2010-06-17, Systemet, 14:18 (Swedish)
Uppsok
Technology
Supervisors
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Available from: 2010-07-01 Created: 2010-07-01 Last updated: 2010-09-27Bibliographically approved

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CiteExportLink to record
Permanent link

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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