SEMANTICS-PROVIDED ENVIRONMENT VIEWS FOR NORMALITY ANALYSIS-BASED INTELLIGENT SURVEILLANCE

Nowadays, the design and development of intelligent surveillance systems is a hot research topic thanks to the recent advances in related fields such as computer perception, artificial intelligence, and distributed devices infrastructures. These systems are gradually going from the classic CCTV passive surveillance systems towards systems which are capable of offering automatic interpretation of the events occurred in a monitored environment and decision support information based on the data obtained from a number of heterogeneous perception devices. In this work, we introduce the formal definition of an intermediate layer in the architecture of an intelligent surveillance system, of which purpose is to provide the components responsible for performing the reasoning processes with the data from the environment they need. Such data is provided by means of environment views, which are data objects that contain not only data from different sensors, but also associated semantics which depends on the particular context in which the analysis of the normality of a concept is performed.