Event detection from video using answer set programming

Understanding of the visual world is not limited to recognizing individual object instances, but also extends to how those objects interact in the scene, which implies recognizing events happening in the scene. In this paper we present an approach for identifying complex events in videos, starting from object detection using a state-of-the-art object detector (YOLO), providing a set of candidate objects. We provide a logic based representation of events by using a realization of the Event Calculus that allows us to define complex events in terms of logical rules. Axioms of the calculus are encoded in a logic program under Answer Set semantics in order to reason and query over the extracted events. The applicability of the framework is demonstrated over the scenario of recognizing car parking on a handicap slot.