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ICIP
2006
IEEE

Light and Fast Statistical Motion Detection Method Based on Ergodic Model

15 years 10 months ago
Light and Fast Statistical Motion Detection Method Based on Ergodic Model
In this paper, we propose a light and fast pixel-based statistical motion detection method based on a background subtraction procedure. The statistical representation of the background relies on its spatial color distributions herein modeled by a mixture of Gaussians. The Gaussian parameters are obtained after segmenting one reference frame with an unsupervised Bayesian approach whose parameter estimation step is ensured by the ? -Means and the Iterated Conditional Estimation (ICE) algorithms. Since the motion detection function only depends on a global mixture of ? Gaussians, only a few bits per pixel need to be stored in memory. Our method achieves real-time performances, especially when look up tables are used to store pre-calculated data. Results have been obtained on synthetic and real video sequences and compared with other statistical methods.
Pierre-Marc Jodoin, Max Mignotte, Janusz Konrad
Added 22 Oct 2009
Updated 22 Oct 2009
Type Conference
Year 2006
Where ICIP
Authors Pierre-Marc Jodoin, Max Mignotte, Janusz Konrad
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