• DocumentCode
    3586305
  • Title

    Implementation of pedestrian detection using a CENTRIST-ROI in embedded environment

  • Author

    Yun-seop Hwang ; Chang-min Jung ; Tae-ryong Park ; Kwang-yeob Lee

  • Author_Institution
    Dept. of Comput. Eng., SeoKyeong Univ., Seoul, South Korea
  • fYear
    2014
  • Firstpage
    50
  • Lastpage
    51
  • Abstract
    This paper proposes a pedestrian detection algorithm to which ROI was applied to implement pedestrian detection that is suitable for the embedded environment. Pedestrian detection has computations for unnecessary areas because the entire input images are computed to find pedestrians in the given images. In this paper, a pedestrian detection algorithm that is ideal for the embedded environment is proposed which reduced computations for unnecessary areas by applying ROI. The CENTIRST descriptor method was used for the pedestrian detection algorithm, which was implemented using 512×360 pixel images on an ALDEBARAN board. The proposed pedestrian detection with ROI showed a 16% improved performance of 3.6 frames per second compared to the conventional method.
  • Keywords
    object detection; pedestrians; ALDEBARAN board; CENTIRST descriptor method; CENTRIST-ROI; embedded environment; pedestrian detection; Computational modeling; census transform histogram; embedded; feature; pedestrian detection; region of interest;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SoC Design Conference (ISOCC), 2014 International
  • Type

    conf

  • DOI
    10.1109/ISOCC.2014.7087589
  • Filename
    7087589