Automatic Clustering Method of Abnormal Crowd Flow Pattern Detection

To ensure the safety of pedestrians in crowds under emergency situation is one of the most important concerns of researchers of building safety, traffic facility design as well as pedestrian traffic planning. Simulations as a consequence have been extensively studied to locate potential locations where danger might happen. However when abnormal pedestrian flow pattern occurs, control or guidance methods should be provided to other pedestrians based on the real-time information about the flow pattern. Thus in the present paper an automatically clustering method for detecting abnormal flow pattern is proposed. The method takes into account the interrelation between individual behavior and global pedestrian flow pattern. As a result it is indicated by the experimental and testing videos that the method is robust and efficient.