• DocumentCode
    607696
  • Title

    A pedestrian detection system with weak classifiers

  • Author

    Tetik, Y.E. ; Bolat, B.

  • Author_Institution
    Multimedya Sinyal Analiz Laboratuari, Yildiz Teknik Univ., İstanbul, Turkey
  • fYear
    2013
  • fDate
    24-26 April 2013
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In this paper, a pedestrian detection system which uses sliding window approach to detect pedestrians in still digital images is presented. The proposed pedestrian detection system combines weak classifiers in an Adaboost like novel way to create a strong classifier. Besides, rectangle ratios and discrete cosine transform coefficients are used as features with the well-known rectangle differences method.
  • Keywords
    discrete cosine transforms; image classification; object detection; pedestrians; digital image; discrete cosine transform coefficient; pedestrian detection system; rectangle difference method; rectangle ratio; sliding window; weak classifier; Abstracts; Boosting; Computer vision; Computers; Conferences; Digital images; Pattern recognition; adaboost; pedestrian detection system; rectangle differences; rectangle ratios; sliding window approach; weak classifiers;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications Conference (SIU), 2013 21st
  • Conference_Location
    Haspolat
  • Print_ISBN
    978-1-4673-5562-9
  • Electronic_ISBN
    978-1-4673-5561-2
  • Type

    conf

  • DOI
    10.1109/SIU.2013.6531357
  • Filename
    6531357