Spatio-temporal Background Models for Outdoor Surveillance

• Main Author: Pless Robert
• Format: Article
• Language: English
• Published: SpringerOpen 2005-01-01
• Series: EURASIP Journal on Advances in Signal Processing
• Subjects: anomaly detection; dynamic backgrounds; spatio-temporal image processing; background subtraction; real-time application
• Online Access: http://dx.doi.org/10.1155/ASP.2005.2281

<p/> <p>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.</p>