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Qualitative multi-scale feature hierarchies for object tracking
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.ORCID iD: 0000-0002-9081-2170
1999 (English)In: SCALE-SPACE THEORIES IN COMPUTER VISION, Elsevier, 1999, 117-128 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper shows how the performance of feature trackers can be improved by building a view-based object representation consisting of qualitative relations between image structures at different scales. The idea is to track all image features individually, and to use the qualitative feature relations for resolving ambiguous matches and for introducing feature hypotheses whenever image features are mismatched or lost. Compared to more traditional work on view-based object tracking, this methodology has the ability to handle semi-rigid objects and partial occlusions. Compared to trackers based on three-dimensional object models, this approach is much simpler and of a more generic nature. A hands-on example is presented showing how an integrated application system can be constructed from conceptually very simple operations.

Place, publisher, year, edition, pages
Elsevier, 1999. 117-128 p.
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 1682
National Category
Computer Vision and Robotics (Autonomous Systems) Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-51770ISI: 000170515400011ISBN: 3-540-66498-X (print)OAI: oai:DiVA.org:kth-51770DiVA: diva2:464973
Conference
2nd International Conference on Scale Space Theory in Computer Vision (Scale-Space 99) SEP 26-27, 1999 CORFU, GREECE
Note

QC 20111214

Available from: 2011-12-14 Created: 2011-12-14 Last updated: 2016-05-12Bibliographically approved

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fulltext(340 kB)51 downloads
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Lindeberg, Tony

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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More styles
Language
  • de-DE
  • en-GB
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Output format
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