What are the problems?

Big data is a big problem. The amount of available data is essential for decision making in a modern world. But it also means more effort and resources are required to extract what is most useful.

This is particularly important for operational decision making. Full Motion Video (FMV) and other assets are essential for providing operational decision-making information. But, the analysts tasked with extracting this information are heavily burdened by multiple persistent video feeds. While highly trained and very good at what they do, the amount of information an analyst uses is growing and they are often tasked with monitoring video feeds for over 10 hours at a time.


What is C-CORE doing?

C-CORE has developed a novel framework for the automatic detection, tracking, and pattern analysis of vehicles in FMV. The resulting information are stored in a spatio-temporal asset catalog (STAC) for visualization in GIS software.

The detection and tracking of vehicles were based on modern machine learning techniques but were identified as components that will continuously update, upgrade, and become better over time. By ensuring that all components of the framework understand the asset catalog, the framework allows for these components to be changed when needed. It also allows for the detection, tracking, and pattern analysis of other objects by adding these components to the framework. The STAC catalog uses best practices and open source structures to handle data, meaning that integrating into modern or legacy systems is possible.


What does this mean for users of FMV?

It means that the human analysts can spend more time on the important decision making tasks for which they are trained and where they excel. The framework that C-CORE has developed can take over the routine detection and tracking of objects and, based on the pattern analysis, can alert the analyst when abnormal patterns are identified. This will reduce the cognitive burden of analysts and allow them to focus on critical decision making.