Chronicle Recognition Improvement Using Temporal Focusing and Hierarchization

This article falls under the problem of the symbolic monitoring of real-time complex systems or of video interpretation systems. Among the various techniques used for the on-line monitoring, we are interested here in the temporal scenario recognition. In order to reduce the complexity of the recognition and, consequently, to improve its performance, we explore two methods: the first one is the focus on particular events (in practice, uncommon ones) and the second one is the factorization of common temporal scenarios in order to do a hierarchical recognition. In this article, we present both concepts and merge them to propose a focused hierarchical recognition. This approach merges and generalizes the two main approaches in symbolic recognition of temporal scenarios: the Store Totally Recognized Scenarios (STRS) approach and the Store Partially Recognized Scenarios (SPRS) approach.