• DocumentCode
    3119292
  • Title

    Computationally efficient classification of human transport mode using micro-doppler signatures

  • Author

    Garreau, Guillaume ; Nicolaou, Nicoletta ; Andreou, Charalambos ; D´Urbal, Cyrille ; Stuarts, Guillermo ; Georgiou, Julius

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Cyprus, Nicosia, Cyprus
  • fYear
    2011
  • fDate
    23-25 March 2011
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In this paper we present a micro-Doppler (mD) system and a computationally efficient classifier for the purpose of distinguishing different means of transport for human beings (pedestrians, inline skaters and cyclists) based on their mD time-frequency signatures. Accuracies as high as 97% are obtained while keeping the overall computational cost low.
  • Keywords
    Doppler shift; road accidents; road safety; road traffic; signal classification; surveillance; time-frequency analysis; ultrasonic transducers; human transport mode classification; mD time-frequency signatures; microDoppler signatures; ultrasonic transducer; Computers; Image segmentation; Lead; Legged locomotion; Spectrogram; Transmitters; Micro-Doppler; spectrogram; standard deviation; transport mode; ultrasonic device;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Sciences and Systems (CISS), 2011 45th Annual Conference on
  • Conference_Location
    Baltimore, MD
  • Print_ISBN
    978-1-4244-9846-8
  • Electronic_ISBN
    978-1-4244-9847-5
  • Type

    conf

  • DOI
    10.1109/CISS.2011.5766136
  • Filename
    5766136
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3119292