High Level Event Detection Based on Spatial Occupancy and Interpersonal Relationships

This paper describes a new approach for eventdetection in video sequences. A tracking algorithm for obliquecamera setups is initially used to extract trajectories in a trainingperiod, and a map of spatial occupancy of the scene is built. In thetest stage, Voronoi Diagrams are used to obtain some informationregarding interpersonal relationships, such as distances fromneighbors, formation and classification of groups. A variety ofcomplex events can be detected through a query formulated bythe user, that may combine concurrent or sequential occurrencesof simpler events based on either spatial occupancy or interpersonalrelationships (e.g. group formation in a region with smallspatial occupancy). These queries can be used to detect eventson-the-fly as the video is processed, or applied to stored videodatabases.