Abstract
The Eigenbackground model is often stated to perform better than pixel-based methods when illumination variations occur. However, it has originally one demerit, that foreground objects must be small. This paper presents an original improvement of the Eigenbackground model, dealing with large and fast moving foreground objects. The method generates background images using the Nelder-Mead Simplex algorithm and a dynamic masking procedure. Experiments show that the proposed method performs as well as the state-of-the-art Eigenbackground improvements in the case of slowly moving objects, and achieves better results for quickly moving objects.
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Quivy, CH., Kumazawa, I. (2011). Background Images Generation Based on the Nelder-Mead Simplex Algorithm Using the Eigenbackground Model. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2011. Lecture Notes in Computer Science, vol 6753. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21593-3_3
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DOI: https://doi.org/10.1007/978-3-642-21593-3_3
Publisher Name: Springer, Berlin, Heidelberg
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