Abstract:
Our objective is to ensure high level of security in public places using static
PTZ camera and robust detection and tracking algorithm for video sequences
and also to generate the multi model background subtraction approach that can
handle dynamic scenes. In this paper we are focussing to design the robust
foreground and background detection technique using the statistical approach
and implement it on the different indoor environments. Among all familiar
background subtraction approach our proposed method used Gaussian mixture
model and predictive filters to detect and track objection successive frames.
To test the performance of our algorithm we will take the standard test
sequences and own datasets. We will analyze our algorithm with the
qualitative and quantitative approaches. so, our aim is to develop such an
smart surveillance system that can not only analyze but also to interpret and
act with reference to the object beheviour against illumination changes, clutter
background, moving background, occlusions and complex silhouette.
