Aggregated Dynamic Background Modeling

13 years 7 months ago
Aggregated Dynamic Background Modeling
Standard practices in background modeling learn a separate model for every pixel in the image. However, in dynamic scenes the connection between an observation and the place where it was observed is much less important and is usually random. For example, a wave observed in an ocean scene could easily have been observed at another place in the image. Moreover, during a limited learning period, we cannot expect to observe at every pixel all the possible background behaviors. We therefore develop in this paper a background model in which observations are decoupled from the place in the image where they were observed. A single non-parametric model is used to describe the dynamic region of the scene, aggregating the observations from the whole region. Using high-order features, we demonstrate the feasibility of our approach on challenging ocean scenes using only grayscale information.
Amit Adam, Ehud Rivlin, Ilan Shimshoni
Added 22 Oct 2009
Updated 27 Oct 2009
Type Conference
Year 2006
Where ICIP
Authors Amit Adam, Ehud Rivlin, Ilan Shimshoni
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