• DocumentCode
    3597378
  • Title

    Vehicle Classification in Video Based on Shape Analysis

  • Author

    Can Nguyen Van ; Cuong Nguyen Ngoc

  • Author_Institution
    People´s Police Univ. of Technol. & Logistics, BacNinh, Vietnam
  • fYear
    2014
  • Firstpage
    151
  • Lastpage
    157
  • Abstract
    This paper aims at presenting some methods of representing image´s features that help detect and classify vehicles from video. Proposed methods include: Method of representing shape, contour of vehicle or block of vehicle that can be classified. Paramaters of the Image´s length in combination with parmaters of visual length of object that can used to classify object type or separate object. Use genaral deformable model of vehicle for allowing to be completely or partially occluding in the image. Apply some proposed methods of representing vehicle for vehicle recognition and classification system in traffic video. This paper also proposes a general working frame for the video - based traffic density detection and vehicle classification system in observation region. System was experimentally installed and obtained good results about the level of accuracy.
  • Keywords
    automobiles; image classification; image representation; image sequences; road traffic; traffic engineering computing; video signal processing; completely occluded image; genaral deformable model; image feature representation; image length; object type classification; observation region; partially occluded image; shape analysis; shape representation; traffic video; vehicle block; vehicle classification system; vehicle contour; vehicle detection; vehicle recognition system; vehicle representation; video-based traffic density detection system; visual length; Cameras; Deformable models; Feature extraction; Motorcycles; Roads; Shape; Car Counting; Contour Analysis; Optical Flow; Shape Detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Modelling Symposium (EMS), 2014 European
  • Print_ISBN
    978-1-4799-7411-5
  • Type

    conf

  • DOI
    10.1109/EMS.2014.27
  • Filename
    7153990