Detecting anomalous human interactions using laser range-finders

We present a laser range-finder-based system for tracking people in an outdoor environment and detecting interactions between them. The system does not use identities of people for tracking. Observed tracks are automatically segmented into individual activities using an entropy-based measure (Jensen-Shannon divergence (Lin, J, 1991)). Two people situated close to each other throughout the duration of an activity represents an interaction. The observed activities are combined using a hierarchical clustering algorithm to generate a representative set. The frequency of occurrence of these activities is modeled by a Poisson distribution. During the monitoring phase, this model is used to compute the probability of observing the detected activities and interactions; an anomaly is flagged if this probability falls below a threshold. Experimental results from an outdoor courtyard environment are described where the system indicates anomalies when there is a sudden increase in the number of people in the environment or in the number of interactions. This detection occurs without giving the system any a priori concepts of space occupancy.