• DocumentCode
    3579980
  • Title

    Deformable parts model for people detection in heavy machines applications

  • Author

    Manh-Tuan Bui ; Fremont, Vincent ; Boukerroui, Djamal ; Letort, Pierrick

  • Author_Institution
    Heudiasyc, Univ. de Technol. de Compiegne (UTC), Compiegne, France
  • fYear
    2014
  • Firstpage
    389
  • Lastpage
    394
  • Abstract
    In this paper we focus on the evaluation of the deformable part model (DPM) proposed by Felzenszwalb et al. [IO] in the context of vision-based people detection in heavy machines applications. The proposed system uses a single fisheye camera to provide a wide field-of-view (FOV) at low cost. However, the fisheye optical distortions present several difficulties for image processing and object recognition. The DPM approach shows important flexibility when dealing with varying object´s form. It gives good performances on people detection when images present strong fisheye distortions. Base on the analysis of DPM in the context of fisheye image, we proposed an adaptive detector which is more suitable.
  • Keywords
    computer vision; object detection; object recognition; DPM approach; FOV; adaptive detector; deformable parts model; fisheye optical distortions; heavy machines applications; image processing; object recognition; single fisheye camera; vision-based people detection; wide field-of-view; Cameras; Context; Deformable models; Detectors; Optical distortion; Training; Vectors; Heavy machines; deformable part model; fisheye images; histogram of oriented gradients; latent support vector machine; pedestrian detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Automation Robotics & Vision (ICARCV), 2014 13th International Conference on
  • Type

    conf

  • DOI
    10.1109/ICARCV.2014.7064337
  • Filename
    7064337