• DocumentCode
    3448895
  • Title

    An Infrared Pedestrians Image Segmentation Algorithm

  • Author

    Dai Qin

  • Author_Institution
    Coll. of Inf., Shenyang Inst. of Eng., Shenyang, China
  • fYear
    2013
  • fDate
    1-3 Nov. 2013
  • Firstpage
    111
  • Lastpage
    114
  • Abstract
    In order to address the problem that the pedestrian segmentation in infrared image is easy to be interfered by the human pose and noise, this paper presents a pedestrian segmentation algorithm in infrared images employing super pixel and conditional random filed. Owing to accelerate the computation, the algorithm employs the simple linear iterative clustering algorithm to divide the image into some super pixels firstly. So as to represent the posterior of a distribution of the image, CRF model is applied to depict the configuration of super pixels in image. Finally we select the label in all of the possible states as the new label which has the minimum energy value in CRF model.
  • Keywords
    image segmentation; infrared imaging; iterative methods; pedestrians; conditional random filed; image distribution; infrared pedestrians image segmentation algorithm; linear iterative clustering algorithm; Clustering algorithms; Computational modeling; Computer vision; Image color analysis; Image segmentation; Noise; CRF; Infrared Image segmentation; Pedestrians; Superpixel;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Networks and Intelligent Systems (ICINIS), 2013 6th International Conference on
  • Conference_Location
    Shenyang
  • Print_ISBN
    978-1-4799-2808-8
  • Type

    conf

  • DOI
    10.1109/ICINIS.2013.35
  • Filename
    6754684