• DocumentCode
    2394262
  • Title

    A method of type recognition using probabilistic constraint support vector machine

  • Author

    Jie, Man

  • Author_Institution
    Eng. Training, Yantai Univ., Yantai, China
  • fYear
    2012
  • fDate
    19-20 May 2012
  • Firstpage
    1796
  • Lastpage
    1799
  • Abstract
    A new support vector machine classifier for recognition of vehicle type which has been captured from traffic scene images. A new support vector machine classifier is presented with probabilistic constrains which presence probability of samples in each class is determined based on a distribution function. Noise is caused to found incorrect support vectors thereupon margin can not be maximized. In the proposed method, constraints boundaries and constraints occurrence have probability density functions which it helps for achieving maximum margin.
  • Keywords
    image recognition; probability; support vector machines; traffic engineering computing; vehicles; SVM classifier; constraints boundaries; constraints occurrence; distribution function; maximum margin; probabilistic constraint support vector machine; probability density functions; traffic scene images; vehiche type recognition; Feature extraction; Optimization; Pattern recognition; Probabilistic logic; Reliability; Support vector machines; Vehicles; Machine identification; Pattern recognition; Probabilistic constraints; Support vector machine; Vehicle type recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems and Informatics (ICSAI), 2012 International Conference on
  • Conference_Location
    Yantai
  • Print_ISBN
    978-1-4673-0198-5
  • Type

    conf

  • DOI
    10.1109/ICSAI.2012.6223393
  • Filename
    6223393