• DocumentCode
    248563
  • Title

    Pedestrian counting based on spatial and temporal analysis

  • Author

    Zhongjie Yu ; Chen Gong ; Jie Yang ; Li Bai

  • Author_Institution
    Instn. of Image Process. & Pattern Recognition, Shanghai Jiao Tong Univ., Shanghai, China
  • fYear
    2014
  • fDate
    27-30 Oct. 2014
  • Firstpage
    2432
  • Lastpage
    2436
  • Abstract
    Pedestrian counting is an important component of video processing. Existing works with overhead cameras are mainly based on visual tracking, the robustness of which is rather limited. By proposing the novel spatial-temporal matrix, this paper aims to count pedestrians without tracking. As a result, a more robust and efficient pedestrian counting algorithm can be developed. Extensive experiment reveal that our system achieves satisfying performances in terms of both accuracy and efficiency.
  • Keywords
    matrix algebra; pedestrians; support vector machines; video surveillance; pedestrian counting algorithm; spatial-and-temporal analysis; spatial-temporal matrix; support vector machine; video camera; video processing; video surveillance; visual tracking; Bandwidth; Cameras; Clustering algorithms; Conferences; Feature extraction; Real-time systems; Support vector machines; Mean-shift Clustering; Pedestrian Counting; Spatial and Temporal Analysis; Support Vector Machine; Video Surveillance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2014 IEEE International Conference on
  • Conference_Location
    Paris
  • Type

    conf

  • DOI
    10.1109/ICIP.2014.7025492
  • Filename
    7025492