The invention is suitable for video monitoring technologies and relates to a method and an apparatus for crowd behavior analysis in video monitoring. The method comprises: obtaining a video stream and dividing each frame of image in the video stream into image sub-blocks with different perspective degrees by taking human height as a size reference by row; extracting deep neural network features in the image sub-blocks; classifying and optimizing the deep neural network features, obtaining a corresponding vector feature set, establishing SVR mathematical models of different kernel functions according to the vector feature set, and making statistics on the number of people in crowds with different density; and adopting a camera calibration method for obtaining coordinate vectors of the deep neural network features, comparing displacements of the deep neural network features of the two continuous frames of image sub-blocks, and calculating a moving direction and a moving speed of the crowd according to the displacement. According to the method and the apparatus, the crowd in the video monitoring is tracked and analyzed to obtain feature information, such as the moving speed, the moving direction, the number of people and the like, of the crowd, the feature information and historical data are analyzed and compared, a state of the crowd is judged, and an alarm is given for an abnormal event.