Surveillance on pedestrian flows in crowded areas is of significance for various security tasks. This problem involves two parts: evaluation of crowdedness and detection of abnormality, where a lot of motion information needs to be studied. This paper defines a crowd energy to deal with crowd modeling and processing in the real-time surveillance. With wavelet analysis of the energy curve, a new approach is presented for monitoring two categories of abnormal events of the scene. The result of a metro video surveillance system has demonstrated the effectiveness of the approach.