Biometric feature detection from surveillance data using non-calibrated techniques

Olli Rantula*, Jorma Skytta

*Tämän työn vastaava kirjoittaja

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference contributionScientificvertaisarvioitu

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 konferenssijulkaisuussa
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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