Advanced video analytics
Luca Greco, Pierluigi Ritrovato, Mario Vento · 2017
During the last decades the interest in the development of surveillance systems capable of autonomously performing video analytics task has become prominent in the scientific community, both for real time analysis and post event forensics. In this paper, we propose a novel video analytics framework where the output of a tracking algorithm on a sequence captured from a video surveillance camera is semantically annotated according to a custom ontology, allowing advanced analytics functionalities. Our approach is based on semantic web standards that guarantee wide interoperability.