• DocumentCode
    3681373
  • Title

    Fast Human Detection Using LDA via L1-Norm

  • Author

    Xiao Pu;Xiaoshuang Shi;Zhenhua Guo;Jie Zhou

  • Author_Institution
    Grad. Sch. at Shenzhen, Tsinghua Univ., Shenzhen, China
  • fYear
    2014
  • fDate
    5/1/2014 12:00:00 AM
  • Firstpage
    206
  • Lastpage
    209
  • Abstract
    Fast detection is of vital importance in human detection sometimes. Considering the high dimensions of the features widely used in human detection, it will severely slow the detection speed. Therefore, in this paper, we try to find a way by using Linear Discriminant Analysis(LDA) via L1-norm regularization to solve this problem. It reduces the dimension of feature from 3780 to 150 before classification, and gets a more fast speed then SVM and LDA, while keeps a competitive accuracy.
  • Keywords
    "Support vector machines","Feature extraction","Accuracy","Training","Histograms","Computer vision","Testing"
  • Publisher
    ieee
  • Conference_Titel
    Service Sciences (ICSS), 2014 International Conference on
  • ISSN
    2165-3828
  • Type

    conf

  • DOI
    10.1109/ICSS.2014.31
  • Filename
    7312317
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3681373