Detecting unusual events in video sequences is very challenging due to cluttered background, the difficulties of accurate extraction and tracking of moving objects, illumination change, etc. In this work, we focus on detecting strong changes in spatial relationships between moving objects in video sequences, with a limited knowledge of the objects. In this approach, the spatial relationships between two objects of interest are modeled using angle and distance histograms as examples. To evaluate the evolution of the spatial relationships during time, the distances between two angle or distance histograms at two different instants in time are estimated. In addition, a combination approach is proposed to combine the evolution of directional (angle) and metric (distance) relationships. Studying the evolution of the spatial relationships during time allows us to detect the ruptures in such spatial relationships. This study can constitute a promising step toward event detection in video sequences, with few a priori models on the objects.