Real time visual surveillance system for human detection

This paper proposes a real time visual surveillance system for human detection this interest needs in many applications where human entry is restricted. In order to develop a real time system initially wavelet transform based multiple features obtained from three layers of each image sample which forms training input to the SVM classifier. Finally, we used trained recognizer to identify whether there is somebody broken into object region. If there is, the automatic warning device gives the alarm, which guarantees a real-time surveillance.