Abstract
Smart surveillance systems developed in recent years have made enormous contributions to providing safety and management
of crowds. The aim of this study is to observe and try to understand how crowd movements presented in a video sequence show behaviour.
For this end, the motion data at pixel level among the consecutive frames is obtained using optical flow initially. Then, this motion data is
associated using the particle advection method and stable as well as moving areas in the image are obtained. After, the moving areas
clustered using Mean-Shift method are described and classified as parabola, in addition to the studies in the literature. At the end of the
study, the method developed was tested over UCF as well as Pets2009 datasets and the results are presented.