Abnormal behavior identification method based on motion constraints

The invention relates to an abnormal behavior identification method based on motion constraints, and belongs to the field of video monitoring. The abnormal behavior identification method comprises a training process. The training process comprises the following steps that 1, the inputted first set of video frame images are calibrated by adopting a rapid calibration method; 2, background modeling is performed on the calibrated inputted video frame images, and optical flow features are extracted from the frame images by using an optical flow method simultaneously; 3, the optical flow features in the foreground are analyzed and selected by using the motion constraints of pedestrians; and 4, the selected optical flow features are studied by using an SVM so that SVM classifier model parameters which can be used for abnormal behavior identification are obtained. The abnormal behavior identification method also comprises a detection process. In the detection process, a second set of videos are inputted, and the used SVM parameters are obtained in the training process and used for detection and judgment of the model parameters. Optical flow feature calculation is optimized, noise optical flow features are eliminated and the optical flow features of the pedestrians are enabled to be more obvious. Besides, running and other abnormal behaviors can be judged.