Σ-Δ background subtraction and the Zipf law

Authors:
Antoine Manzanera
Affiliations:
ENSTA, Elec. and Comp. Sc. lab, Paris, France
Venue:
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
Year:
2007

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Abstract

The Σ-Δ background estimation is a simple non linear method of background subtraction based on comparison and elementary increment/decrement. We propose here some elements of justification of this method with respect to statistical estimation, compared to other recursive methods: exponential smoothing, Gaussian estimation. We point out the relation between the Σ-Δ estimation and a probabilistic model: the Zipf law. A new algorithm is proposed for computing the background/foreground classification as the pixel-level part of a motion detection algorithm. Comparative results and computational advantages of the method are commented.