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Accumulation of Different Visual Feature Descriptors in a Coherent Framework

  • Jeppe Barsøe Jessen
  • Florian Pilz
  • Dirk Kraft
  • Nicolas Pugeault
  • Norbert Krüger
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6688)

Abstract

We present a temporal accumulation scheme which disambiguates different kinds of visual 3D descriptors within one coherent framework. The accumulation consists of a twofold process: First, by means of a Bayesian filtering outliers become eliminated and second, the precision of the extracted information becomes enhanced by means of an unscented Kalman filtering process. It is a particular property of our algorithm to be able to deal with different kinds of visual descriptors by the very same mechanism. We show quantitative and qualitative results.

Keywords

Motion Estimation Rigid Body Motion Unscented Kalman Filter Visual Descriptor Dual Quaternion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Jeppe Barsøe Jessen
    • 1
  • Florian Pilz
    • 2
  • Dirk Kraft
    • 1
  • Nicolas Pugeault
    • 3
  • Norbert Krüger
    • 1
  1. 1.Mærsk Mc-Kinney Møller InstituteUniversity of Southern DenmarkOdenseDenmark
  2. 2.Department of Architecture, Design & Media TechnologyAalborg UniversityDenmark
  3. 3.Centre for Vision, Speech and Signal ProcessingUniversity of SurreyUnited Kingdom

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