• DocumentCode
    676222
  • Title

    Utilization of Directional Properties of Optical Flow for Railway Crossing Occupancy Monitoring

  • Author

    Silar, Zdenek ; Dobrovolny, M.

  • Author_Institution
    Dept. of Inf. Technol., Univ. of Pardubice, Pardubice, Czech Republic
  • fYear
    2013
  • fDate
    16-18 Dec. 2013
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This article deals with the obstacle detection on a railway crossing (clearance detection). Detection is based on the optical flow estimation and classification of the flow vectors by K means clustering algorithm. For classification of passing vehicles is used optical flow direction determination. The optical flow estimation is based on a modified Lucas-Kanade method.
  • Keywords
    image classification; image sequences; matrix algebra; object detection; pattern clustering; rail traffic; railways; traffic engineering computing; background matrix; clearance detection; directional property utilization; flow vector classification; k-means clustering algorithm; modified Lucas-Kanade method; obstacle detection; optical flow direction determination; optical flow estimation; passing vehicle classification; railway crossing occupancy monitoring; Adaptive optics; Clustering algorithms; Computer vision; Estimation; Image motion analysis; Optical imaging; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    IT Convergence and Security (ICITCS), 2013 International Conference on
  • Conference_Location
    Macao
  • Type

    conf

  • DOI
    10.1109/ICITCS.2013.6717896
  • Filename
    6717896