Explainable Anomaly Detection in Videos Based on the Description of Atomic Actions

Anomaly detection in surveillance videos is an exhaustive and tedious task to be performed manually by humans. Many methods have been proposed to detect anomalous events by learning normal patterns and differentiate them from abnormal ones. However, these methods often suffer from false alarms, as human behaviors and environments can change over time. In addition, these methods fail to discriminate the types of anomalies that can occur, especially in anomalies performed by humans. This work presents an approach to detect anomalous events based on atomic action descriptions. It combines a tracking people method with atomic action detection and recognition network to understand video events and generate atomic descriptions. Besides detecting the anomalies, the proposed approach can also describe the anomalous action with human attributes in natural language. Anomalies are detected based on the generated descriptions of the scene. Experimental results show the effectiveness of our approach, presenting an average F1-Score of 87%.

A Cook’s Tour of Equational Axiomatizations for Prefix Iteration

Prefix iteration is a variation on the original binary version of the<br />Kleene star operation P*Q, obtained by restricting the first argument to be an atomic action, and yields simple iterative behaviours that can be equationally characterized by means of finite collections of axioms. In this paper, we present axiomatic characterizations for a significant fragment of the notions of equivalence and preorder in van Glabbeek's linear-time/branching-time spectrum over Milner's basic CCS extended with prefix iteration. More precisely, we consider ready simulation, simulation, readiness, trace and language semantics, and provide complete (in)equational axiomatizations for each of these notions over BCCS with prefix iteration. All of the axiom systems we present are finite, if so is the set of atomic actions under consideration.