Automated Video Surveillance System For Human Motion Detection With Face Detection

Abstract

Automated video surveillance systems are of most importance in the field of security. The task of detecting
moving objects in surveillance. Video is create a base for higher level intelligence applications, Now a days, video
surveillance is an important security asset to control theft, trespassing or traffic monitoring, banks, department stores,
highways, crowded public places and borders. In this thesis, our objective is to design a complete framework able to
automatically detect and recognize humans in video sequences acquired with a static camera. The aimed practical
application for this framework is its use as an automatic intelligent video surveillance system. In video surveillance,
detection of moving objects from a video is necessary for object classification, target tracking, activity recognition, as
well as behavior understanding. For better result, I have used this proposed technique: combination of Gaussian
mixture model technique & optical flow technique. A face detection system is a computer application for
automatically detecting a human face from digital image or video frame from a video source. As a conclusion, this is
aimed to researchers interested to research on the basic idea of human motion detection algorithm using image.