Automatically Identifying Pedestrian Behaviors in Crowds

We present a real-time algorithm to automatically classify the dynamic behavior or personality of a pedestrian based on his or her movements in a crowd video. We present a statistical scheme that dynamically learns the behavior of every pedestrian in a scene and computes that pedestrian's motion model. This model is combined with global crowd characteristics to compute the movement patterns and motion dynamics, which can also be used to predict the crowd movement and behavior.