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A robust and computationally efficient motion detection algorithm based on sigma-delta background estimation

Abstract : This paper presents a new algorithm to detect moving objects within a scene acquired by a stationary camera. A simple recursive non linear operator, the Sigma-Delta filter, is used to estimate two orders of temporal statistics for every pixel of the image. The output data provide a scene characterization allowing a simple and efficient pixel-level change detection framework. For a more suitable detection, exploiting spatial correlation in these data is necessary. We use them as a multiple observation field in a Markov model, leading to a spatiotemporal regularization of the pixel-level solution. This method yields a good trade-off in terms of robustness and accuracy, with a minimal cost in memory and a low computational complexity.
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Antoine Manzanera, Julien Richefeu. A robust and computationally efficient motion detection algorithm based on sigma-delta background estimation. Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP'04), Dec 2004, Kolkata, India. ⟨hal-01222695⟩

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