Biometric feature detection from surveillance data using non-calibrated techniques

Olli Rantula*, Jorma Skytta

*Tämän työn vastaava kirjoittaja

    Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference article in proceedingsScientificvertaisarvioitu

    Abstrakti

    The development of high quality video surveillance systems provides the ability to perform measurements from image data. This paper describes and demonstrates the extraction of basic human biometric features from surveillance video camera data using an uncalibrated single-view surveillance camera system. Perspective-based photogrammetric techniques are applied in situations where only minimal real world information is available. This information usually includes the reference height and two orthogonal sets of parallel lines on a reference plane. These all must be detectable both in the real world and be in the field of-view of the camera. Using this type of setup, the orthogonal distance from the reference plane can be computed at any scene point. The measured biometric features include height and body dimensions. Additionally the gait features and the walking profile can be estimated when photogrammetry techniques are extended from a single image to a video stream. Such information can be used for forensic investigation and in various types of other applications where photogrammetric information is needed. This can be done without further information about the camera calibration or position.

    AlkuperäiskieliEnglanti
    Otsikko2017 4TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND INTEGRATED NETWORKS (SPIN)
    KustantajaIEEE
    Sivut629-634
    Sivumäärä6
    ISBN (painettu)978-1-5090-2797-2
    DOI - pysyväislinkit
    TilaJulkaistu - 2017
    OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
    TapahtumaInternational Conference on Signal Processing and Integrated Networks - Noida, Intia
    Kesto: 2 helmik. 20173 helmik. 2017
    Konferenssinumero: 4

    Conference

    ConferenceInternational Conference on Signal Processing and Integrated Networks
    LyhennettäSPIN
    Maa/AlueIntia
    KaupunkiNoida
    Ajanjakso02/02/201703/02/2017

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