• DocumentCode
    1775493
  • Title

    Automated image tracking based on the CAMSHIFT algorithm with adaboost and target trajectory and size estimation

  • Author

    Chi-Juang Hsieh ; Kai-Yew Lum

  • Author_Institution
    Dept. of Electr. Eng., Nat. Chi Nan Univ., Nantou, Taiwan
  • fYear
    2014
  • fDate
    18-20 June 2014
  • Firstpage
    918
  • Lastpage
    923
  • Abstract
    In order to overcome a shortcoming of traditional CAMSHIFT which requires manual target designation and object color similarity between frames, this paper proposes an image tracking algorithm by a combination of CAMSHIFT with Adaboost object detection and the Kalman estimator. The proposed method alleviates loss-of-track problems caused by accelerating target motion and color noise. Robustness against occlusion is also improved, while the number of iterations that CAMSHIFT requires is reduced.
  • Keywords
    learning (artificial intelligence); object detection; target tracking; Adaboost object detection; CAMSHIFT algorithm; Kalman estimator; automated image tracking algorithm; color noise; frames; object color similarity; occlusion; robustness; size estimation; target designation; target motion; target trajectory; Acceleration; Face; Image color analysis; Interference; Kalman filters; Object detection; Target tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control & Automation (ICCA), 11th IEEE International Conference on
  • Conference_Location
    Taichung
  • Type

    conf

  • DOI
    10.1109/ICCA.2014.6871044
  • Filename
    6871044