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    • CAS: Computer Science: Technical Reports
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    •   OpenBU
    • College of Arts and Sciences
    • Computer Science
    • CAS: Computer Science: Technical Reports
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    Segmenting Foreground Objects from a Dynamic Textured Background via a Robust Kalman Filter

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    Date Issued
    2003-07-18
    Author(s)
    Zhong, Jing
    Sclaroff, Stan
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    Permanent Link
    https://hdl.handle.net/2144/1514
    Abstract
    The algorithm presented in this paper aims to segment the foreground objects in video (e.g., people) given time-varying, textured backgrounds. Examples of time-varying backgrounds include waves on water, clouds moving, trees waving in the wind, automobile traffic, moving crowds, escalators, etc. We have developed a novel foreground-background segmentation algorithm that explicitly accounts for the non-stationary nature and clutter-like appearance of many dynamic textures. The dynamic texture is modeled by an Autoregressive Moving Average Model (ARMA). A robust Kalman filter algorithm iteratively estimates the intrinsic appearance of the dynamic texture, as well as the regions of the foreground objects. Preliminary experiments with this method have demonstrated promising results.
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    • CAS: Computer Science: Technical Reports [585]


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