Abstract
Particle filtering based motion tracking needs the extraction of the region of moving object to assign particles for moving object. To extract the moving object, a background subtraction is often used. However, it is difficult to extract the moving object when illumination changes during motion. Updating background image using RANSAC has been proposed to solve this problem, but it is still difficult for RANSAC to update the background image with high accuracy when many exception values are included in the data for updating background. In addition, another constraint includes such that the first background image is necessary for updating background image to extract the moving object. This paper proposes an extended new approach to update the background image with high accuracy using the data which excepts the exception values based on the tracking result with particle filtering. PSA (Pixel State Analysis) is further introduced to distribute particles before updating the first background, which can assign particles without preparing background image in advance.
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Iwahori, Y., Kurahashi, W., Fukui, S., Woodham, R.J. (2009). Updating Background Image for Motion Tracking Using Particle Filter. In: Nakamatsu, K., Phillips-Wren, G., Jain, L.C., Howlett, R.J. (eds) New Advances in Intelligent Decision Technologies. Studies in Computational Intelligence, vol 199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00909-9_39
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DOI: https://doi.org/10.1007/978-3-642-00909-9_39
Publisher Name: Springer, Berlin, Heidelberg
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