• DocumentCode
    3056551
  • Title

    Local dependency analysis in probabilistic scene estimation

  • Author

    Grundmann, Thilo ; Eidenberger, Robert ; Zollner, Raoul D.

  • Author_Institution
    Inf. & Commun., Siemens Corp. Technol., Munich
  • fYear
    2008
  • fDate
    27-29 May 2008
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    A general solution to the problem of jointly estimating the state of multiple entities is regarded computationally challenging at the time. Most solutions are based on the application of wide assumptions of independence. In many situations and constellations of entities, this is sufficient and leads to high quality results. In some situations as occlusion for instance the assumption of independence is violated heavily resulting in considerable errors. The proposed approach considers local dependencies, allowing to increase the accuracy of the estimation punctually, depending on application requirements, such as high precision localization for grasping operations or rough precision for semantic localization.
  • Keywords
    computer vision; object detection; application requirements; local dependencies; local dependency analysis; probabilistic scene estimation; rough precision; semantic localization; Bayesian methods; Communications technology; Filters; Information analysis; Layout; Mechatronics; Mobile robots; State estimation; State-space methods; Target tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronics and Its Applications, 2008. ISMA 2008. 5th International Symposium on
  • Conference_Location
    Amman
  • Print_ISBN
    978-1-4244-2033-9
  • Electronic_ISBN
    978-1-4244-2034-6
  • Type

    conf

  • DOI
    10.1109/ISMA.2008.4648815
  • Filename
    4648815