Abstract:
Background subtraction is one of the main techniques to extract moving objects from background scenes. A mixture of Gaussians is a common model for background subtraction. There are several parameters involved in such a model. Obviously, the assignment of initial values to these parameters affects the accuracy of background subtraction. In this paper, we analyze in detail the impact of different initial parameter values based on our model implementation. Both indoor and outdoor video sequences have been tested. This parameter value analysis provides suggestions how to choose suitable initial parameter values, assign reasonable thresholds which ensure better results, while using a mixture of Gaussians model in video surveillance applications.
Description:
You are granted permission for the non-commercial reproduction, distribution, display, and performance of this technical report in any format, BUT this permission is only for a period of 45 (forty-five) days from the most recent time that you verified that this technical report is still available from the original CITR web site; http://citr.auckland.ac.nz/techreports/ under terms that include this permission. All other rights are reserved by the author(s).