Abstract
Automatic counting of people in the crowd using surveillance visual camera is very useful in effective crowd management, security surveillance, and many more applications. In this paper, we have proposed an intelligent framework to automate the process of people counting in the surveillance video. Foreground (moving people) segmentation from the video is done by combination of different foreground estimation techniques. Texture analysis and foreground pixel area for different segmentation techniques are used to extract the useful features. Neural Network is trained on these features and people counting accuracy of more than 96% is achieved on a benchmark video. [Arif M Saqib M, Basalamah S, Naeem A. Counting of Moving People in the Video using Neural Network System. Life Sci J 2012; 9(3): 1384-1392] (ISSN: 1097-8135). http://www.lifesciencesite.com. 201