• DocumentCode
    1537630
  • Title

    Data-driven MCMC sampling for vision-based 6D SLAM

  • Author

    Min, Jeeeun ; Kim, Jung-Ho ; Shin, Seung Heon ; Kweon, In-So

  • Author_Institution
    Dept. of Electr. Eng., KAIST, Daejeon, South Korea
  • Volume
    48
  • Issue
    12
  • fYear
    2012
  • Firstpage
    687
  • Lastpage
    689
  • Abstract
    An efficient sampling technique for estimating camera motion is presented. For this purpose, Markov chain Monte Carlo (MCMC) sampling is incorporated into the data-driven proposal distribution in order to improve the SLAM performance. Experimental results using both synthetic and real datasets demonstrate the efficiency of the proposed method.
  • Keywords
    Markov processes; Monte Carlo methods; SLAM (robots); cameras; motion estimation; robot vision; Markov chain Monte Carlo sampling; camera motion estimation; data-driven MCMC sampling technique; data-driven proposal distribution; vision-based 6D SLAM;
  • fLanguage
    English
  • Journal_Title
    Electronics Letters
  • Publisher
    iet
  • ISSN
    0013-5194
  • Type

    jour

  • DOI
    10.1049/el.2012.0897
  • Filename
    6215301
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1537630