Page 32 - Read Online
P. 32

Xu et al. J Surveill Secur Saf 2020;1:16-33  I  http://dx.doi.org/10.20517/jsss.2020.04                                                              Page 25






























                                                 Figure 7. Schematic block diagram

               research object of this algorithm. The algorithm is mainly used to locate the escape center of the crowd,
               and the escape center is defined as the position where the intersection of the motion vector is the densest.
               Therefore, the removal of wild intersections should remove a smaller number of intersections in the search
               window. The graphical method used in this paper uses many experiments to obtain empirical thresholds to
               measure the denseness of intersections to assist in removing wild intersections [Figure 7].


               4 EXPERIMENTAL EVALUATION
               Step 1: Select the video. In the experiments, 10 segments of video were selected to test three kinds of
               abnormal behaviors. The test video mainly came from a bank monitoring video, and some videos were
               from the crime scene monitoring. Moreover, the surveillance video was recorded by Haikang or Dahua
               cameras. Some test videos were taken by digital cameras, and these video formats were different, including
               AVl, MP4, DAV, etc. In addition, the system unified the video sources to AVI format for easy processing.
               The number of pedestrians appearing in the selected video, the time of appearance of the pedestrian, the
               video resolution, etc. were all random and there was no law. In addition, because shadow removal is not the
               focus of this paper, to reduce the impact of shadow on the algorithm, only video with less obvious shadow
               was selected when selecting video.


               Step 2: Parameter configuration. First, the camera corresponding to the selected video was calibrated, and
               after the coordinate conversion was completed, the actual coordinate matrix was saved as an XML file (the
               file name is the camera name, and the file suffix is .xml). Then, the estimated target imaging size, frame
               interval, monitoring area, abnormal behavior type, etc. were saved in the PAR file (the file has the same
               name as the test video file and the file suffix is .par).


               Step 3: The result of manual statistics. The video was observed by the human eye, and the manual statistical
               result was recorded in the MTR file (the file has the same name as the test video file, and the file suffix is
               .mtr). Manual statistics were needed to record the type of abnormal behavior, start time, and end time.
               Finally, the number of samples with abnormal behavior (abnormality) and no abnormal behavior (normal)
               in the selected video were counted according to the behavior type. The statistical results are shown in
               Tables 1-3.
   27   28   29   30   31   32   33   34   35   36   37