Human interaction analysis based on walking pattern transitions

We propose a method that analyzes interaction between pedestrians based on their trajectories obtained using sensors such as cameras. Our objective is to understand the mutual relationship between pedestrians and to detect anomalous events in a video sequence. Under such situations, we can observe the interaction between a pair of pedestrians. This paper proposes a set of features that measures the interaction between pedestrians. We assume that a person is likely to change his/her walking patterns when he/she has been influenced by another person. Based on this assumption, the proposed method first extracts the transition points of a walking pattern from trajectories of two pedestrians and then measures the strength of the influence using the temporal and spatial closeness between them. Finally, experimental results obtained from actual videos demonstrate the method's effectiveness in understating mutual relationships and detecting anomalous events.