id: 05053529
dt: j
an: 05053529
au: Pless, Robert
ti: Spatio-temporal background models for outdoor surveillance.
so: EURASIP J. Appl. Signal Process. 2005, No. 14, 2281-2291 (2005).
py: 2005
pu: Hindawi Publishing Corporation, New York, NY
la: EN
cc: 
ut: anomaly detection; dynamic backgrounds; spatio-temporal image processing;
    background subtraction; real-time application
ci: 
li: doi:10.1155/ASP.2005.2281
ab: Summary: Video surveillance in outdoor areas is hampered by consistent
    background motion which defeats systems that use motion to identify
    intruders. While algorithms exist for masking out regions with motion,
    a better approach is to develop a statistical model of the typical
    dynamic video appearance. This allows the detection of potential
    intruders even in front of trees and grass waving in the wind, waves
    across a lake, or cars moving past. In this paper we present a general
    framework for the identification of anomalies in video, and a
    comparison of statistical models that characterize the local video
    dynamics at each pixel neighborhood. A real-time implementation of
    these algorithms runs on an 800 MHz laptop, and we present qualitative
    results in many application domains.
rv: