• DocumentCode
    2543389
  • Title

    Feature enhancement for mean-shift based object tracking

  • Author

    Gamage, D.S. ; Samarakoon, B. ; Dabarera, R. ; Handagala, S.M. ; Rodrigo, R.

  • Author_Institution
    Dept. of Electron. & Telecommun. Eng., Univ. of Moratuwa, Moratuwa, Sri Lanka
  • fYear
    2010
  • fDate
    17-19 Dec. 2010
  • Firstpage
    282
  • Lastpage
    285
  • Abstract
    In object tracking identifying the best feature which discriminates object and background improves the performance. Most of the existing methods do not consider the suitability of such features for the tracker. Here we enhance the discriminative features which elevate the tracker performance. To accommodate object and background variations over time we dynamically update the best feature using a distance measure. We demonstrate the performance of the resulting systems on the UNIVERSITÄT KARLSRUHE Image Sequences.
  • Keywords
    feature extraction; image sequences; object detection; tracking; UNIVERSITÄT KARLSRUHE image sequence; background variations; discriminative features; feature enhancement; mean shift based object tracking; Histograms; Pixel; Robustness; Object tracking; dynamic update; feature enhancement; sigmoid image;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Automation for Sustainability (ICIAFs), 2010 5th International Conference on
  • Conference_Location
    Colombo
  • Print_ISBN
    978-1-4244-8549-9
  • Type

    conf

  • DOI
    10.1109/ICIAFS.2010.5715674
  • Filename
    5715674
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2543389