• DocumentCode
    732345
  • Title

    Motion classification of pedestrian walking behaviors on the sidewalk

  • Author

    Gihyun Han ; Heejae Choi ; Bongsob Song

  • Author_Institution
    Dept. of Mech. Eng., Ajou Univ., Suwon, South Korea
  • fYear
    2015
  • fDate
    7-10 July 2015
  • Firstpage
    228
  • Lastpage
    231
  • Abstract
    This paper proposes a motion classification algorithm of pedestrian walking behavior by fusing radar and vision sensors. Under the situation that the pedestrian is detected by both two heterogeneous sensors, it will be discussed how quickly the intention of pedestrian on the sidewalk, e.g., stop, crossing, and walking along the road, is determined. While most of previous researches use lateral position of pedestrian as a feature for classification, the velocity with respect to lane at the sidewalk is estimated and used as an additional feature. Support vector machine as a classifier is used for motion classification of walking behaviors. Finally, the proposed algorithm will be validated via driving test data.
  • Keywords
    gait analysis; image motion analysis; image sensors; pedestrians; radar imaging; road traffic; sensor fusion; support vector machines; traffic engineering computing; driving test data; heterogeneous sensors; motion classification algorithm; pedestrian walking behaviors; radar; sidewalk; support vector machine; vision sensors; Classification algorithms; Estimation; Legged locomotion; Radar; Sensors; Support vector machines; Vehicles; Automatic emergency braking; Convex optimization; Motion classification; Support vector machine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Ubiquitous and Future Networks (ICUFN), 2015 Seventh International Conference on
  • Conference_Location
    Sapporo
  • ISSN
    2288-0712
  • Type

    conf

  • DOI
    10.1109/ICUFN.2015.7182539
  • Filename
    7182539