Moving Object Detection Using an Adaptive Background Modeling in Dynamic Scene

Year 2017, Volume: 2 Issue: 1, 161 - 166, 25.02.2017

M.fatih Savas

Abstract

Determination of moving foreground objects in dynamic scenes
for video surveillance systems is still a problem can not be resolved exactly.
In the literature; pixel-based, block-based and texture-based methods have been
proposed  to solve this problem. The
method we propose will be block-based method which can be applied to real time
in dynamic scenes. We have created non-overlapped  blocks with the averages the pixels in the
gray level. We used this average value to generate the background model based
on a modified original KDE (Kernel Density Estimation) method. To determine the
moving foreground objects and  to update
background model, we use an adaptive parameter which is determined  according to 
the number of changes in the state of this pixel during the last N
frames. Performance evaluation of the proposed method is tested by background
methods in literature without applying post-processing techniques. Experimental
results demonstrate the effectiveness and robustness of our method.

Keywords

Background modeling, Moving object, Background update

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