Automatic Reasoning about Causal Events in Surveillance Video

Neil M. Robertson, Ian D. Reid
2011 EURASIP Journal on Image and Video Processing  
We present a new method for explaining causal interactions among people in video. The input to the overall system is video in which people are low/medium resolution. We extract and maintain a set of qualitative descriptions of single-person activity using the low-level vision techniques of spatiotemporal action recognition and gaze-direction approximation. This models the input to the "sensors" of the person agent in the scene and is a general sensing strategy for a person agent in a variety of
more » ... application domains. The information subsequently available to the reasoning process is deliberately limited to model what an agent would actually be able to sense. The reasoning is therefore not a classical "all-knowing" strategy but uses these "sensed" facts obtained from the agents, combined with generic domain knowledge, to generate causal explanations of interactions. We present results from urban surveillance video.
doi:10.1155/2011/530325 fatcat:v6gt42qhlrgnzbdlq7nuodrbnq