Long video data resulted from the use of cameras lab activities as a action recording. We present a new framework for recognizing student activities from the class. In this system we improve intelligent mechanism, top low level motion detection algorithm and feature extraction. We recognize the frame difference and feature selection for human activities that permits recognition. The detection of human activity from videos is very complicated appropriate to the complex reality of events,
