Kernel Particle Filter for Visual Quality Inspection from Monocular Intensity Images

  • Dirk Stößel
  • Gerhard Sagerer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4174)


Industrial part assembly has come a long way and so has visual quality inspection. Nevertheless, the key issue in automated industrial quality inspection, i.e. the pose recovery of the objects under inspection, is still a challenging task for assemblies with more than two rigid parts. This paper presents a system for the pose recovery of assemblies consisting of an arbitrary number of rigid subparts. In an offline stage, the system extracts edge information from CAD models. Online, the system uses a novel kernel particle filter to recover the full pose of the visible subparts of the assembly under inspection. The accuracy of the pose estimation is evaluated and compared to state-of-the-art systems.


Kernel Density Estimate Bandwidth Parameter Rigid Part Dual Quaternion Posterior Probability Density 
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 2006

Authors and Affiliations

  • Dirk Stößel
    • 1
  • Gerhard Sagerer
    • 1
  1. 1.Applied Computer Science, Faculty of TechnologyBielefeld UniversityBielefeldGermany

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