Behaviour Recognition using the Event Calculus

摘要

We present a system for recognising human behaviour given a symbolic representation of surveillance videos. The input of our system is a set of time-stamped short-term behaviours, that is, behaviours taking place in a short period of time - walking, running, standing still, etc - detected on video frames. The output of our system is a set of recognised long-term behaviours - fighting, meeting, leaving an object, collapsing, walking, etc - which are pre-defined temporal combinations of short-term behaviours. The definition of a long-term behaviour, including the temporal constraints on the short-term behaviours that, if satisfied, lead to the recognition of the long-term behaviour, is expressed in the Event Calculus. We present experimental results concerning videos with several humans and objects, temporally overlapping and repetitive behaviours.