Video-surveillance system for tracking a person by estimating the trajectory

This paper we propose a simple and efficient video surveillance system which detects and tracks a person in a video stream. Object detection is the most important and crucial step for any video surveillance system. In this paper, we separate foreground and background by using the statistical model of Gaussian Mixture (GMM). Interests points are identified in the detected regions (foreground) using the Harris detector. The analysis of connected components detected by subtracting the background allows grouped the pixels of moving objects in order to extract the center of gravity. Then, a boundary box is used to limit the area of connected components in order to detect the coordinates of the gravity center of the moving person. Finally, by projection in Euclidean plan we can get the trajectory of the person in motion and compute the Euclidean distance crossed in the scene. © 2005 - 2013 JATIT & LLS. All rights reserved.