• DocumentCode
    1655736
  • Title

    Multiple object tracking with energetic particle filtering and GVF-snake

  • Author

    Chunli, Dong ; Yuning, Dong ; Li, Wang ; Jie, Liu

  • Author_Institution
    Coll. of Commun. & Inf. Eng., Nanjing Univ. of Posts & Telecommun., Nanjing
  • fYear
    2008
  • Firstpage
    1075
  • Lastpage
    1078
  • Abstract
    A novel adaptive multi-object tracking algorithm with modified particle filtering and GVF-snake is proposed. Through the combination of modified particle filtering and GVF-snake, a novel energetic particle filtering (EPF) object tracking algorithm is proposed; and the multiple objects can be tracked with modified K-means clustering and energetic particle filtering (EPF). The tracking tactic for partially occluded objects is also proposed to overcome the effects such as occlusions in a complex environment. Experiments show that the proposed algorithm can fully utilize the information of mostly non-occluded object contour points in the entire tracking process, and obtain better tracking results even though the tracked objects are occluded for long time.
  • Keywords
    filtering theory; target tracking; GVF-snake; energetic particle filtering; gradient vector flow; modified K-means clustering; multiple object tracking; object contour points; Active contours; Adaptive filters; Clustering algorithms; Deformable models; Educational institutions; Filtering algorithms; Information filtering; Information filters; Intelligent transportation systems; Particle tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, 2008. ICSP 2008. 9th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-2178-7
  • Electronic_ISBN
    978-1-4244-2179-4
  • Type

    conf

  • DOI
    10.1109/ICOSP.2008.4697315
  • Filename
    4697315