We propose a method that not only identifies humans in the environment and their location, but can also classify and identify their activity, providing a threat assessment. Such assessments would be useful for both human and vehicle activities in crowds to determine aberrant behavior from previously identified truth data sets. Such aberrant behavior would lead to IED detection, RPG detection, and the recognition of suicide bombers, before the explosives and planted and activated.

The heuristics needed involve recognition of information bearing features in the environment, and the determination of how those features relate to each other over time (that is, gesture recognition). This paper addresses the mathematical development necessary to create a behavior and gait recognition sensor system that has its foundation on the recognition of combined individual gestures.