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Erschienen in:
2005 | OriginalPaper | Buchkapitel
A Kalman Filter Based Background Updating Algorithm Robust to Sharp Illumination Changes
verfasst von : Stefano Messelodi, Carla Maria Modena, Nicola Segata, Michele Zanin
Erschienen in: Image Analysis and Processing – ICIAP 2005
Verlag: Springer Berlin Heidelberg
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A novel algorithm, based on Kalman filtering is presented for updating the background image within video sequences. Unlike existing implementations of the Kalman filter for this task, our algorithm is able to deal with both gradual and sudden global illumination changes. The basic idea is to measure global illumination change and to use it as an external control of the filter. This allows the system to better fit the assumptions about the process to be modeled. Moreover, we propose methods to estimate measurement noise variance and to deal with the problem of saturated pixels, to improve the accuracy and robustness of the algorithm. The algorithm has been successfully tested in a traffic surveillance task by comparing it to a background updating algorithm, based on Kalman filtering, taken from literature.